Discrete mathematics Books

Book SynopsisEvery year there is at least one combinatorics problem in each of the major international mathematical olympiads. These problems can only be solved with a very high level of wit and creativity. This book explains all the problem-solving techniques necessary to tackle these problems, with clear examples from recent contests. It also includes a large problem section for each topic, including hints and full solutions so that the reader can practice the material covered in the book.​ The material will be useful not only to participants in the olympiads and their coaches but also in university courses on combinatorics.Trade ReviewFrom the reviews: “Soberón (Univ. College London, UK) presents tools, techniques, and some tricks to tackle problems of varying difficulty in combinatorial mathematics in this well-written book. … Salient features include the wealth of examples, exercises, and problems and two additional chapters with hints and solutions to the problems. Valuable for all readers interested in combinatorics and useful as a course resource on the subject. Summing Up: Highly recommended. Upper-division undergraduate through professional mathematics collections.” (D. V. Chopra, Choice, Vol. 51 (4), December, 2013)Table of ContentsIntroduction.- 1 First concepts.- 2 The pigeonhole principle.- 3 Invariants.- 4 Graph theory.- 5 Functions.- 6 Generating Functions.- 7 Partitions.- 8 Hints for the problems.- 9 Solutions to the problems.- Notation.- Further reading.- Index. ​

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Book SynopsisCryptography has become essential as bank transactions, credit card infor-mation, contracts, and sensitive medical information are sent through inse-cure channels. This book is concerned with the mathematical, especially algebraic, aspects of cryptography. It grew out of many courses presented by the authors over the past twenty years at various universities and covers a wide range of topics in mathematical cryptography. It is primarily geared towards graduate students and advanced undergraduates in mathematics and computer science, but may also be of interest to researchers in the area. Besides the classical methods of symmetric and private key encryption, the book treats the mathematics of cryptographic protocols and several unique topics such as Group-Based Cryptography Gröbner Basis Methods in Cryptography Lattice-Based Cryptography

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Book SynopsisIn the two-volume set ‘A Selection of Highlights’ we present basics of mathematics in an exciting and pedagogically sound way. This volume examines many fundamental results in Geometry and Discrete Mathematics along with their proofs and their history. In the second edition we include a new chapter on Topological Data Analysis and enhanced the chapter on Graph Theory for solving further classical problems such as the Traveling Salesman Problem.

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Book SynopsisThis book provides an introduction to hypergraphs, its aim being to overcome the lack of recent manuscripts on this theory. In the literature hypergraphs have many other names such as set systems and families of sets. This work presents the theory of hypergraphs in its most original aspects, while also introducing and assessing the latest concepts on hypergraphs. The variety of topics, their originality and novelty are intended to help readers better understand the hypergraphs in all their diversity in order to perceive their value and power as mathematical tools. This book will be a great asset to upper-level undergraduate and graduate students in computer science and mathematics. It has been the subject of an annual Master's course for many years, making it also ideally suited to Master's students in computer science, mathematics, bioinformatics, engineering, chemistry, and many other fields. It will also benefit scientists, engineers and anyone else who wants to understand hypergraphs theory.Trade ReviewFrom the reviews:“This book addresses the mathematics and theory of hypergraphs. The target audience includes graduate students and researchers with an interest in math and computer science (CS). … I expect readers of this book will be motivated to advance this field, which in turn can advance other sciences.” (Hsun-Hsien Chang, Computing Reviews, January, 2014)“The aim of this book is to introduce the basic concepts of hypergraphs, to present the knowledge of the theory and applications of hypergraphs in other fields. … This book is useful for anyone who wants to understand the basics of hypergraph theory. It is mainly for math and computer science majors, but it may also be useful for other fields which use the theory. … appropriate for both researchers and graduate students. It is very well-written and proofs are stated in a clear manner.” (Somayeh Moradi, zbMATH, Vol. 1269, 2013)Table of ContentsHypergraphs: basic concepts.- Hypergraphs: first properties.- Hypergraph coloring.- Some particular hypergraphs.- Reduction-contraction of Hypergraph.- Dirhypergraphs: basic concepts.- Applications of hypergraph theory : a brief overview.

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Book SynopsisThis book provides an introduction to hypergraphs, its aim being to overcome the lack of recent manuscripts on this theory. In the literature hypergraphs have many other names such as set systems and families of sets. This work presents the theory of hypergraphs in its most original aspects, while also introducing and assessing the latest concepts on hypergraphs. The variety of topics, their originality and novelty are intended to help readers better understand the hypergraphs in all their diversity in order to perceive their value and power as mathematical tools. This book will be a great asset to upper-level undergraduate and graduate students in computer science and mathematics. It has been the subject of an annual Master's course for many years, making it also ideally suited to Master's students in computer science, mathematics, bioinformatics, engineering, chemistry, and many other fields. It will also benefit scientists, engineers and anyone else who wants to understand hypergraphs theory.Trade ReviewFrom the reviews:“This book addresses the mathematics and theory of hypergraphs. The target audience includes graduate students and researchers with an interest in math and computer science (CS). … I expect readers of this book will be motivated to advance this field, which in turn can advance other sciences.” (Hsun-Hsien Chang, Computing Reviews, January, 2014)“The aim of this book is to introduce the basic concepts of hypergraphs, to present the knowledge of the theory and applications of hypergraphs in other fields. … This book is useful for anyone who wants to understand the basics of hypergraph theory. It is mainly for math and computer science majors, but it may also be useful for other fields which use the theory. … appropriate for both researchers and graduate students. It is very well-written and proofs are stated in a clear manner.” (Somayeh Moradi, zbMATH, Vol. 1269, 2013)Table of ContentsHypergraphs: basic concepts.- Hypergraphs: first properties.- Hypergraph coloring.- Some particular hypergraphs.- Reduction-contraction of Hypergraph.- Dirhypergraphs: basic concepts.- Applications of hypergraph theory : a brief overview.

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Book SynopsisTransactions are a concept related to the logical database as seen from the perspective of database application programmers: a transaction is a sequence of database actions that is to be executed as an atomic unit of work. The processing of transactions on databases is a well- established area with many of its foundations having already been laid in the late 1970s and early 1980s.The unique feature of this textbook is that it bridges the gap between the theory of transactions on the logical database and the implementation of the related actions on the underlying physical database. The authors relate the logical database, which is composed of a dynamically changing set of data items with unique keys, and the underlying physical database with a set of fixed-size data and index pages on disk. Their treatment of transaction processing builds on the “do-redo-undo” recovery paradigm, and all methods and algorithms presented are carefully designed to be compatible with this paradigm as well as with write-ahead logging, steal-and-no-force buffering, and fine-grained concurrency control.Chapters 1 to 6 address the basics needed to fully appreciate transaction processing on a centralized database system within the context of our transaction model, covering topics like ACID properties, database integrity, buffering, rollbacks, isolation, and the interplay of logical locks and physical latches. Chapters 7 and 8 present advanced features including deadlock-free algorithms for reading, inserting and deleting tuples, while the remaining chapters cover additional advanced topics extending on the preceding foundational chapters, including multi-granular locking, bulk actions, versioning, distributed updates, and write-intensive transactions.This book is primarily intended as a text for advanced undergraduate or graduate courses on database management in general or transaction processing in particular.Table of Contents1 Transactions on the Logical Database.- 2 Operations on the Physical Database.- 3 Logging and Buffering.- 4 Transaction Rollback and Restart Recovery.- 5 Transactional Isolation.- 6 Lock-Based Concurrency Control.- 7 B-Tree Traversals.- 8 B-Tree Structure Modifications.- 9 Advanced Locking Protocols.- 10 Bulk Operations on B-Trees.- 11 Online Index Construction and Maintenance.- 12 Concurrency Control by Versioning.- 13 Distributed Transactions.- 14 Transactions in Page-Server Systems.- 15 Processing of Write-Intensive Transactions.

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Book SynopsisThis textbook treats two important and related matters in convex geometry: the quantification of symmetry of a convex set—measures of symmetry—and the degree to which convex sets that nearly minimize such measures of symmetry are themselves nearly symmetric—the phenomenon of stability. By gathering the subject’s core ideas and highlights around Grünbaum’s general notion of measure of symmetry, it paints a coherent picture of the subject, and guides the reader from the basics to the state-of-the-art. The exposition takes various paths to results in order to develop the reader’s grasp of the unity of ideas, while interspersed remarks enrich the material with a behind-the-scenes view of corollaries and logical connections, alternative proofs, and allied results from the literature. Numerous illustrations elucidate definitions and key constructions, and over 70 exercises—with hints and references for the more difficult ones—test and sharpen the reader’s comprehension.The presentation includes: a basic course covering foundational notions in convex geometry, the three pillars of the combinatorial theory (the theorems of Carathéodory, Radon, and Helly), critical sets and Minkowski measure, the Minkowski–Radon inequality, and, to illustrate the general theory, a study of convex bodies of constant width; two proofs of F. John’s ellipsoid theorem; a treatment of the stability of Minkowski measure, the Banach–Mazur metric, and Groemer’s stability estimate for the Brunn–Minkowski inequality; important specializations of Grünbaum’s abstract measure of symmetry, such as Winternitz measure, the Rogers–Shepard volume ratio, and Guo’s Lp -Minkowski measure; a construction by the author of a new sequence of measures of symmetry, the kth mean Minkowski measure; and lastly, an intriguing application to the moduli space of certain distinguished maps from a Riemannian homogeneous space to spheres—illustrating the broad mathematical relevance of the book’s subject.Trade Review“The book under review is a graduate-level textbook on convexity, which presents the topic from a new and interesting point of view. … The book offers the reader a new approach to the study of convexity, focusing on the important topics of measures of symmetry and stability. It moves from the very beginning background to recent research, and therefore both students and researchers can benefit from it.” (María A. Hernández Cifre, Mathematical Reviews, December, 2016) “This is a graduate-level textbook on convex geometry in finite-dimensional Euclidean spaces, which has some interesting special features. … Each chapter has illustrating figures and concludes with exercises … . The book has a surprising appendix, where certain of the symmetry measures are applied to convex bodies … . This book is an unconventional introduction to convexity, full of appealing intuitive geometry; it may equally well serve the beginner and the experienced researcher in the field.” (Rolf Schneider, zbMATH 1335.52002, 2016)Table of ContentsFirst Things First on Convex Sets.- Affine Diameters and the Critical Set.- Measures of Stability and Symmetry.- Mean Minkowski Measures.

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Book SynopsisThis clearly written textbook presents an accessible introduction to discrete mathematics for computer science students, offering the reader an enjoyable and stimulating path to improve their programming competence. The text empowers students to think critically, to be effective problem solvers, to integrate theory and practice, and to recognize the importance of abstraction. Its motivational and interactive style provokes a conversation with the reader through a questioning commentary, and supplies detailed walkthroughs of several algorithms.This updated and enhanced new edition also includes new material on directed graphs, and on drawing and coloring graphs, in addition to more than 100 new exercises (with solutions to selected exercises).Topics and features: assumes no prior mathematical knowledge, and discusses concepts in programming as and when they are needed; designed for both classroom use and self-study, presenting modular and self-contained chapters that follow ACM curriculum recommendations; describes mathematical processes in an algorithmic manner, often supported by a walkthrough demonstrating how the algorithm performs the desired task; includes an extensive set of exercises throughout the text, together with numerous examples, and shaded boxes highlighting key concepts; selects examples that demonstrate a practical use for the concept in question.Students embarking on the start of their studies of computer science will find this book to be an easy-to-understand and fun-to-read primer, ideal for use in a mathematics course taken concurrently with their first programming course.Table of ContentsAlgorithms, Numbers and MachinesSets, Sequences and CountingBoolean Expressions, Logic and ProofSearching and SortingGraphs and TreesRelations: Especially on (Integer) SequencesSequences and SeriesGenerating Sequences and SubsetsDiscrete Probability and Average Case ComplexityTuring Machines

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Book SynopsisIt is gratifying that this textbook is still sufficiently popular to warrant a third edition. I have used the opportunity to improve and enlarge the book. When the second edition was prepared, only two pages on algebraic geometry codes were added. These have now been removed and replaced by a relatively long chapter on this subject. Although it is still only an introduction, the chapter requires more mathematical background of the reader than the remainder of this book. One of the very interesting recent developments concerns binary codes defined by using codes over the alphabet 7l.4• There is so much interest in this area that a chapter on the essentials was added. Knowledge of this chapter will allow the reader to study recent literature on 7l. -codes. 4 Furthermore, some material has been added that appeared in my Springer Lec­ ture Notes 201, but was not included in earlier editions of this book, e. g. Generalized Reed-Solomon Codes and Generalized Reed-Muller Codes. In Chapter 2, a section on "Coding Gain" ( the engineer's justification for using error-correcting codes) was added. For the author, preparing this third edition was a most welcome return to mathematics after seven years of administration. For valuable discussions on the new material, I thank C.P.l.M.Baggen, I. M.Duursma, H.D.L.Hollmann, H. C. A. van Tilborg, and R. M. Wilson. A special word of thanks to R. A. Pellikaan for his assistance with Chapter 10.Table of Contents1 Mathematical Background.- 1.1. Algebra.- 1.2. Krawtchouk Polynomials.- 1.3. Combinatorial Theory.- 1.4. Probability Theory.- 2 Shannon’s Theorem.- 2.1. Introduction.- 2.2. Shannon’s Theorem.- 2.3. On Coding Gain.- 2.4. Comments.- 2.5. Problems.- 3 Linear Codes.- 3.1. Block Codes.- 3.2. Linear Codes.- 3.3. Hamming Codes.- 3.4. Majority Logic Decoding.- 3.5. Weight Enumerators.- 3.6. The Lee Metric.- 3.7. Comments.- 3.8. Problems.- 4 Some Good Codes.- 4.1. Hadamard Codes and Generalizations.- 4.2. The Binary Golay Code.- 4.3. The Ternary Golay Code.- 4.4. Constructing Codes from Other Codes.- 4.5. Reed—Muller Codes.- 4.6. Kerdock Codes.- 4.7. Comments.- 4.8. Problems.- 5 Bounds on Codes.- 5.1. Introduction: The Gilbert Bound.- 5.2. Upper Bounds.- 5.3. The Linear Programming Bound.- 5.4. Comments.- 5.5. Problems.- 6 Cyclic Codes.- 6.1. Definitions.- 6.2. Generator Matrix and Check Polynomial.- 6.3. Zeros of a Cyclic Code.- 6.4. The Idempotent of a Cyclic Code.- 6.5. Other Representations of Cyclic Codes.- 6.6. BCH Codes.- 6.7. Decoding BCH Codes.- 6.8. Reed—Solomon Codes.- 6.9. Quadratic Residue Codes.- 6.10. Binary Cyclic Codes of Length 2n(n odd).- 6.11. Generalized Reed—Muller Codes.- 6.12. Comments.- 6.13. Problems.- 7 Perfect Codes and Uniformly Packed Codes.- 7.1. Lloyd’s Theorem.- 7.2. The Characteristic Polynomial of a Code.- 7.3. Uniformly Packed Codes.- 7.4. Examples of Uniformly Packed Codes.- 7.5. Nonexistence Theorems.- 7.6. Comments.- 7.7. Problems.- 8 Codes over ?4.- 8.1. Quaternary Codes.- 8.2. Binary Codes Derived from Codes over ?4.- 8.3. Galois Rings over ?4.- 8.4. Cyclic Codes over ?4.- 8.5. Problems.- 9 Goppa Codes.- 9.1. Motivation.- 9.2. Goppa Codes.- 9.3. The Minimum Distance of Goppa Codes.- 9.4. Asymptotic Behaviour of Goppa Codes.- 9.5. Decoding Goppa Codes.- 9.6. Generalized BCH Codes.- 9.7. Comments.- 9.8. Problems.- 10 Algebraic Geometry Codes.- 10.1. Introduction.- 10.2. Algebraic Curves.- 10.3. Divisors.- 10.4. Differentials on a Curve.- 10.5. The Riemann—Roch Theorem.- 10.6. Codes from Algebraic Curves.- 10.7. Some Geometric Codes.- 10.8. Improvement of the Gilbert—Varshamov Bound.- 10.9. Comments.- 10.10.Problems.- 11 Asymptotically Good Algebraic Codes.- 11.1. A Simple Nonconstructive Example.- 11.2. Justesen Codes.- 11.3. Comments.- 11.4. Problems.- 12 Arithmetic Codes.- 12.1. AN Codes.- 12.2. The Arithmetic and Modular Weight.- 12.3. Mandelbaum—Barrows Codes.- 12.4. Comments.- 12.5. Problems.- 13 Convolutional Codes.- 13.1. Introduction.- 13.2. Decoding of Convolutional Codes.- 13.3. An Analog of the Gilbert Bound for Some Convolutional Codes.- 13.4. Construction of Convolutional Codes from Cyclic Block Codes.- 13.5. Automorphisms of Convolutional Codes.- 13.6. Comments.- 13.7. Problems.- Hints and Solutions to Problems.- References.

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Book SynopsisBoth classical geometry and modern differential geometry have been active subjects of research throughout the 20th century and lie at the heart of many recent advances in mathematics and physics. The underlying motivating concept for the present book is that it offers readers the elements of a modern geometric culture by means of a whole series of visually appealing unsolved (or recently solved) problems that require the creation of concepts and tools of varying abstraction. Starting with such natural, classical objects as lines, planes, circles, spheres, polygons, polyhedra, curves, surfaces, convex sets, etc., crucial ideas and above all abstract concepts needed for attaining the results are elucidated. These are conceptual notions, each built "above" the preceding and permitting an increase in abstraction, represented metaphorically by Jacob's ladder with its rungs: the 'ladder' in the Old Testament, that angels ascended and descended... In all this, the aim of the book is to demonstrate to readers the unceasingly renewed spirit of geometry and that even so-called "elementary" geometry is very much alive and at the very heart of the work of numerous contemporary mathematicians. It is also shown that there are innumerable paths yet to be explored and concepts to be created. The book is visually rich and inviting, so that readers may open it at random places and find much pleasure throughout according their own intuitions and inclinations. Marcel Berger is the author of numerous successful books on geometry, this book once again is addressed to all students and teachers of mathematics with an affinity for geometry.Trade Review“It is a must own book for anyone serious about developing a conceptual understanding of the interconnected web of modern geometry and the ever-growing intertwining of geometry with practically all other branches of mathematics. … It is remarkable for a book to provide such a detailed glimpse of contemporary geometry via well developed discussions of so many questions of current interest. It provides the most extensive exposition of geometric thinking I’ve ever seen in a book at this level.” (William H. Barker, MAA Reviews, August, 2017)“Geometry Revealed is to give the reader a feel for the conceptual frameworks of modern geometry, attempting to reach as far as possible with a minimum of assumed knowledge and formal scaffolding. … Geometry Revealed being useful for research mathematicians as a still reasonably up-to-date survey. … Geometry Revealed offered an ascent into the wonders of a new world.” (Danny Yee, Danny Yee’s Book Reviews, dannyreviews.com, July, 2015)“By considering a hierarchy of ‘natural’ geometrical objects … it sets out to investigate significant geometrical problems which are either unsolved or were solved only recently. … it is undoubtedly a major tour de force, and if you really want to gain an idea of where geometry is going in the 21st century, you will find plenty of exquisite material here.” (Gerry Leversha, The Mathematical Gazette, Vol. 96 (356), July, 2012)“The book contains twelve chapters, each of them is a collection of such problems about geometric objects with more and more complexity … . The chapters are independent from each other, any of them can serve as a course. Researchers in geometry can use it as a source for further research. … the book is accessible to a wide audience of people who are interested in geometry.” (János Kincses, Acta Scientiarum Mathematicarum (Szeged), Vol. 78 (1-2), 2012)“‘Geometry Revealed’ is a massive text of 831 pages which is organized in twelve chapters and which additionally provides indices for names, subjects and symbols … throughout the author quite carefully lays out the historical perspective. … a typical chapter starts with an observation or a problem in elementary geometry. Large parts of the text are very accessible, and a reader who likes (mathematical) physics will often get something extra.” (Michael Joswig, Zentralblatt MATH, Vol. 1232, 2012)“The author provides the reader with an enormous amount of detailed information and thus yields deep insight into the various topics. … All in all an overwhelming book which is a must … for everyone having sufficient mathematical knowledge.” (G. Kowol, Monatshefte für Mathematik, Vol. 164 (2), October, 2011)“The book is a very readable account of several branches of geometry, classical and modern, elementary and advanced. … Every chapter is extremely interesting and alive. … The book is rich in ideas, written in an informal style, with no formulae and no unnecessary technical details. … Every part of this book is interesting and should be accessible to a wide audience of mathematicians. … Every mathematician will experience great pleasure in reading this book.” (Athanase Papadopoulos, Mathematical Reviews, Issue 2011 m)Table of ContentsPoints and lines in the plane.- Circles and spheres.- The sphere by itself: can we distribute points on it evenly?.- Conics and quadrics.- Plane curves.- Smooth surfaces.- Convexity and convex sets.- Polygons, polyhedra, polytopes.- Lattices, packings and tilings in the plane.- Lattices and packings in higher dimensions.- Geometry and dynamics I: billiards.- Geometry and dynamics II: geodesic flow on a surface.

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Book SynopsisA matroid is an abstract mathematical structure that captures combinatorial properties of matrices. This book offers a unique introduction to matroid theory, emphasizing motivations from matrix theory and applications to systems analysis. This book serves also as a comprehensive presentation of the theory and application of mixed matrices, developed primarily by the present author in the 1990's. A mixed matrix is a convenient mathematical tool for systems analysis, compatible with the physical observation that "fixed constants" and "system parameters" are to be distinguished in the description of engineering systems. This book will be extremely useful to graduate students and researchers in engineering, mathematics and computer science. From the reviews: "…The book has been prepared very carefully, contains a lot of interesting results and is highly recommended for graduate and postgraduate students." András Recski, Mathematical Reviews Clippings 2000m:93006Table of ContentsPreface I. Introduction to Structural Approach --- Overview of the Book 1 Structural Approach to Index of DAE 1.1 Index of differential-algebraic equations 1.2 Graph-theoretic structural approach 1.3 An embarrassing phenomenon 2 What Is Combinatorial Structure? 2.1 Two kinds of numbers 2.2 Descriptor form rather than standard form 2.3 Dimensional analysis 3 Mathematics on Mixed Polynomial Matrices 3.1 Formal definitions 3.2 Resolution of the index problem 3.3 Block-triangular decomposition II. Matrix, Graph and Matroid 4 Matrix 4.1 Polynomial and algebraic independence 4.2 Determinant 4.3 Rank, term-rank and generic-rank 4.4 Block-triangular forms 5 Graph 5.1 Directed graph and bipartite graph 5.2 Jordan-Holder-type theorem for submodular functions 5.3 Dulmage-Mendelsohn decomposition 5.4 Maximum flow and Menger-type linking 5.5 Minimum cost flow and weighted matching 6 Matroid 6.1 From matrix to matroid 6.2 Basic concepts 6.3 Examples 6.4 Basis exchange properties 6.5 Independent matching problem 6.6 Union 6.7 Bimatroid (linking system) III. Physical Observations for Mixed Matrix Formulation 7 Mixed Matrix for Modeling Two Kinds of Numbers 7.1 Two kinds of numbers 7.2 Mixed matrix and mixed polynomial matrix 8 Algebraic Implications of Dimensional Consistency 8.1 Introductory comments 8.2 Dimensioned matrix 8.3 Total unimodularity of dimensioned matrices 9 Physical Matrix 9.1 Physical matrix 9.2 Physical matrices in a dynamical system IV. Theory and Application of Mixed Matrices 10 Mixed Matrix and Layered Mixed Matrix 11 Rank of Mixed Matrices 11.1 Rank identities for LM-matrices 11.2 Rank identities for mixed matrices 11.3 Reduction to independent matching problems 11.4 Algorithms for the rank 11.4.1 Algorithm for LM-matrices 11.4.2 Algorithm for mixed matrices 12 Structural Solvability of Systems of Equations 12.1 Formulation of structural solvability 12.2 Graphical conditions for structural solvability 12.3 Matroidal conditions for structural solvability 13. Combinatorial Canonical Form of LM-matrices 13.1 LM-equivalence 13.2 Theorem of CCF 13.3 Construction of CCF 13.4 Algorithm for CCF 13.5 Decomposition of systems of equations by CCF 13.6 Application of CCF 13.7 CCF over rings 14 Irreducibility of LM-matrices 14.1 Theorems on LM-irreducibility 14.2 Proof of the irreducibility of determinant 15 Decomposition of Mixed Matrices 15.1 LU-decomposition of invertible mixed matrices 15.2 Block-triangularization of general mixed matrices 16 Related Decompositions 16.1 Partition as a matroid union 16.2 Multilayered matrix 16.3 Electrical network with admittance expression 17 Partitioned Matrix 17.1 Definitions 17.2 Existence of proper block-triangularization 17.3 Partial order among blocks 17.4 Generic partitioned matrix 18 Principal Structures of LM-matrices 18.1 Motivations 18.2 Principal structure of submodular systems 18.3 Principal structure of generic matrices 18.4 Vertical principal structure of LM-matrices 18.5 Horizontal principal structure of LM-matrices V. Polynomial Matrix and Valuated Matroid 19 Polynomial/Rational Matrix 19.1 Polynomial matrix and Smith form 19.2 Rational matrix and Smith-McMillan form at infinity 19.3 Matrix pencil and Kronecker form 20 Valuated Matroid 20.1 Introduction 20.2 Examples 20.3 Basic operations 20.4 Greedy algorithms 20.5 Valuated bimatroid 20.6 Induction through bipartite graphs 20.7 Characterizations 20.8 Further exchange properties 20.9 Valuated independent assignment problem 20.10 Optimality criteria 20.10.1 Potential criterion 20.10.2 Negative-cycle criterion 20.10.3 Proof of the optimality criteria 20.10.4 Extension to VIAP(k) 20.11 Application to triple matrix product 20.12 Cycle-canceling algorithms 20.12.1 Algorithms 20.12.2 Validity of the minimum-ratio cycle algorithm 20.13 Augmenting algorithms 20.13.1 Algorithms 20.13.2 Validity of the augmenting algorithm VI. Theory and Application of Mixed Polynomial Matrices 21 Descriptions of Dynamical Systems 21.1 Mixed polynomial mat

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Book SynopsisThe algorithmic solution of problems has always been one of the major concerns of mathematics. For a long time such solutions were based on an intuitive notion of algorithm. It is only in this century that metamathematical problems have led to the intensive search for a precise and sufficiently general formalization of the notions of computability and algorithm. In the 1930s, a number of quite different concepts for this purpose were pro­ posed, such as Turing machines, WHILE-programs, recursive functions, Markov algorithms, and Thue systems. All these concepts turned out to be equivalent, a fact summarized in Church's thesis, which says that the resulting definitions form an adequate formalization of the intuitive notion of computability. This had and continues to have an enormous effect. First of all, with these notions it has been possible to prove that various problems are algorithmically unsolvable. Among of group these undecidable problems are the halting problem, the word problem theory, the Post correspondence problem, and Hilbert's tenth problem. Secondly, concepts like Turing machines and WHILE-programs had a strong influence on the development of the first computers and programming languages. In the era of digital computers, the question of finding efficient solutions to algorithmically solvable problems has become increasingly important. In addition, the fact that some problems can be solved very efficiently, while others seem to defy all attempts to find an efficient solution, has called for a deeper under­ standing of the intrinsic computational difficulty of problems.Trade ReviewP. Bürgisser, M. Clausen, M.A. Shokrollahi, and T. Lickteig Algebraic Complexity Theory "The book contains interesting exercises and useful bibliographical notes. In short, this is a nice book."—MATHEMATICAL REVIEWS From the reviews: "This book is certainly the most complete reference on algebraic complexity theory that is available hitherto. … superb bibliographical and historical notes are given at the end of each chapter. … this book would most certainly make a great textbook for a graduate course on algebraic complexity theory. … In conclusion, any researchers already working in the area should own a copy of this book. … beginners at the graduate level who have been exposed to undergraduate pure mathematics would find this book accessible." (Anthony Widjaja, SIGACT News, Vol. 37 (2), 2006)Table of Contents1. Introduction.- I. Fundamental Algorithms.- 2. Efficient Polynomial Arithmetic.- 3. Efficient Algorithms with Branching.- II. Elementary Lower Bounds.- 4. Models of Computation.- 5. Preconditioning and Transcendence Degree.- 6. The Substitution Method.- 7. Differential Methods.- III. High Degree.- 8. The Degree Bound.- 9. Specific Polynomials which Are Hard to Compute.- 10. Branching and Degree.- 11. Branching and Connectivity.- 12. Additive Complexity.- IV. Low Degree.- 13. Linear Complexity.- 14. Multiplicative and Bilinear Complexity.- 15. Asymptotic Complexity of Matrix Multiplication.- 16. Problems Related to Matrix Multiplication.- 17. Lower Bounds for the Complexity of Algebras.- 18. Rank over Finite Fields and Codes.- 19. Rank of 2-Slice and 3-Slice Tensors.- 20. Typical Tensorial Rank.- V. Complete Problems.- 21. P Versus NP: A Nonuniform Algebraic Analogue.- List of Notation.

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Book SynopsisThis volume deals with the theory of finite topological spaces and its relationship with the homotopy and simple homotopy theory of polyhedra. The interaction between their intrinsic combinatorial and topological structures makes finite spaces a useful tool for studying problems in Topology, Algebra and Geometry from a new perspective. In particular, the methods developed in this manuscript are used to study Quillen's conjecture on the poset of p-subgroups of a finite group and the Andrews-Curtis conjecture on the 3-deformability of contractible two-dimensional complexes. This self-contained work constitutes the first detailed exposition on the algebraic topology of finite spaces. It is intended for topologists and combinatorialists, but it is also recommended for advanced undergraduate students and graduate students with a modest knowledge of Algebraic Topology.Trade ReviewFrom the reviews:“This book deals with the algebraic topology of finite topological spaces and its applications, and includes well-known results on finite spaces and original results developed by the author. The book is self-contained and well written. It is understandable and enjoyable to read. It contains a lot of examples and figures which help the readers to understand the theory.” (Fumihiro Ushitaki, Mathematical Reviews, March, 2014)“This book illustrates convincingly the idea that the study of finite non-Hausdorff spaces from a homotopical point of view is useful in many areas and can even be used to study well-known problems in classical algebraic topology. … This book is a revised version of the PhD Thesis of the author. … All the concepts introduced with the chapters are usefully illustrated by examples and the recollection of all these results gives a very nice introduction to a domain of growing interest.” (Etienne Fieux, Zentralblatt MATH, Vol. 1235, 2012)Table of Contents1 Preliminaries.- 2 Basic topological properties of finite spaces.- 3 Minimal finite models.- 4 Simple homotopy types and finite spaces.- 5 Strong homotopy types.- 6 Methods of reduction.- 7 h-regular complexes and quotients.- 8 Group actions and a conjecture of Quillen.- 9 Reduced lattices.- 10 Fixed points and the Lefschetz number.- 11 The Andrews-Curtis conjecture.

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Book SynopsisSince the publication of the first edition of our book, geometric algorithms and combinatorial optimization have kept growing at the same fast pace as before. Nevertheless, we do not feel that the ongoing research has made this book outdated. Rather, it seems that many of the new results build on the models, algorithms, and theorems presented here. For instance, the celebrated Dyer-Frieze-Kannan algorithm for approximating the volume of a convex body is based on the oracle model of convex bodies and uses the ellipsoid method as a preprocessing technique. The polynomial time equivalence of optimization, separation, and membership has become a commonly employed tool in the study of the complexity of combinatorial optimization problems and in the newly developing field of computational convexity. Implementations of the basis reduction algorithm can be found in various computer algebra software systems. On the other hand, several of the open problems discussed in the first edition are still unsolved. For example, there are still no combinatorial polynomial time algorithms known for minimizing a submodular function or finding a maximum clique in a perfect graph. Moreover, despite the success of the interior point methods for the solution of explicitly given linear programs there is still no method known that solves implicitly given linear programs, such as those described in this book, and that is both practically and theoretically efficient. In particular, it is not known how to adapt interior point methods to such linear programs.Table of Contents0. Mathematical Preliminaries.- 0.1 Linear Algebra and Linear Programming.- Basic Notation.- Hulls, Independence, Dimension.- Eigenvalues, Positive Definite Matrices.- Vector Norms, Balls.- Matrix Norms.- Some Inequalities.- Polyhedra, Inequality Systems.- Linear (Diophantine) Equations and Inequalities.- Linear Programming and Duality.- 0.2 Graph Theory.- Graphs.- Digraphs.- Walks, Paths, Circuits, Trees.- 1. Complexity, Oracles, and Numerical Computation.- 1.1 Complexity Theory: P and NP.- Problems.- Algorithms and Turing Machines.- Encoding.- Time and Space Complexity.- Decision Problems: The Classes P and NP.- 1.2 Oracles.- The Running Time of Oracle Algorithms.- Transformation and Reduction.- NP-Completeness and Related Notion.- 1.3 Approximation and Computation of Numbers.- Encoding Length of Numbers.- Polynomial and Strongly Polynomial Computations.- Polynomial Time Approximation of Real Numbers.- 1.4 Pivoting and Related Procedures.- Gaussian Elimination.- Gram-Schmidt Orthogonalization.- The Simplex Method.- Computation of the Hermite Normal Form.- 2. Algorithmic Aspects of Convex Sets: Formulation of the Problems.- 2.1 Basic Algorithmic Problems for Convex Sets.- 2.2 Nondeterministic Decision Problems for Convex Sets.- 3. The Ellipsoid Method.- 3.1 Geometric Background and an Informal Description.- Properties of Ellipsoids.- Description of the Basic Ellipsoid Method.- Proofs of Some Lemmas.- Implementation Problems and Polynomiality.- Some Examples.- 3.2 The Central-Cut Ellipsoid Method.- 3.3 The Shallow-Cut Ellipsoid Method.- 4. Algorithms for Convex Bodies.- 4.1 Summary of Results.- 4.2 Optimization from Separation.- 4.3 Optimization from Membership.- 4.4 Equivalence of the Basic Problems.- 4.5 Some Negative Results.- 4.6 Further Algorithmic Problems for Convex Bodies.- 4.7 Operations on Convex Bodies.- The Sum.- The Convex Hull of the Union.- The Intersection.- Polars, Blockers, Antiblockers.- 5. Diophantine Approximation and Basis Reduction.- 5.1 Continued Fractions.- 5.2 Simultaneous Diophantine Approximation: Formulation of the Problems.- 5.3 Basis Reduction in Lattices.- 5.4 More on Lattice Algorithms.- 6. Rational Polyhedra.- 6.1 Optimization over Polyhedra: A Preview.- 6.2 Complexity of Rational Polyhedra.- 6.3 Weak and Strong Problems.- 6.4 Equivalence of Strong Optimization and Separation.- 6.5 Further Problems for Polyhedra.- 6.6 Strongly Polynomial Algorithms.- 6.7 Integer Programming in Bounded Dimension.- 7. Combinatorial Optimization: Some Basic Examples.- 7.1 Flows and Cuts.- 7.2 Arborescences.- 7.3 Matching.- 7.4 Edge Coloring.- 7.5 Matroids.- 7.6 Subset Sums.- 7.7 Concluding Remarks.- 8. Combinatorial Optimization: A Tour d’Horizon.- 8.1 Blocking Hypergraphs and Polyhedra.- 8.2 Problems on Bipartite Graphs.- 8.3 Flows, Paths, Chains, and Cuts.- 8.4 Trees, Branchings, and Rooted and Directed Cuts.- Arborescences and Rooted Cuts.- Trees and Cuts in Undirected Graphs.- Dicuts and Dijoins.- 8.5 Matchings, Odd Cuts, and Generalizations.- Matching.- b-Matching.- T-Joins and T-Cuts.- Chinese Postmen and Traveling Salesmen.- 8.6 Multicommodity Flows.- 9. Stable Sets in Graphs.- 9.1 Odd Circuit Constraints and t-Perfect Graphs.- 9.2 Clique Constraints and Perfect Graphs.- Antiblockers of Hypergraphs.- 9.3 Orthonormal Representations.- 9.4 Coloring Perfect Graphs.- 9.5 More Algorithmic Results on Stable Sets.- 10. Submodular Functions.- 10.1 Submodular Functions and Polymatroids.- 10.2 Algorithms for Polymatroids and Submodular Functions.- Packing Bases of a Matroid.- 10.3 Submodular Functions on Lattice, Intersecting, and Crossing Families.- 10.4 Odd Submodular Function Minimization and Extensions.- References.- Notation Index.- Author Index.

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Book SynopsisThese lecture notes treat polynomial identity rings from both the combinatorial and structural points of view. The greater part of recent research in polynomial identity rings is about combinatorial questions, and the combinatorial part of the lecture notes gives an up-to-date account of recent research. On the other hand, the main structural results have been known for some time, and the emphasis there is on a presentation accessible to newcomers to the subject.Trade ReviewFrom the reviews: “The book under review consists of two excellent monographs on the PI-theory by two leading researchers, V. Drensky and E. Formanek … In summary, both expositions are very well written, and the book is recommended both for graduate students and researchers.” (MATHEMATICAL REVIEWS)Table of ContentsA Combinatorial Aspects in PI-Rings.- Vesselin Drensky.- 1 Basic Properties of PI-algebras.- 2 Quantitative Approach to PI-algebras.- 3 The Amitsur-Levitzki Theorem.- 4 Central Polynomials for Matrices.- 5 Invariant Theory of Matrices.- 6 The Nagata-Higman Theorem.- 7 The Shirshov Theorem for Finitely Generated PI-algebras.- 8 Growth of Codimensions of PI-algebras.- B Polynomial Identity Rings.- Edward Formanek.- 1 Polynomial Identities.- 2 The Amitsur-Levitzki Theorem.- 3 Central Polynomials.- 4 Kaplansky’s Theorem.- 5 Theorems of Amitsur and Levitzki on Radicals.- 6 Posner’s Theorem.- 7 Every PI-ring Satisfies a Power of the Standard Identity.- 8 Azumaya Algebras.- 9 Artin’s Theorem.- 10 Chain Conditions.- 11 Hilbert and Jacobson PI-Rings.- 12 The Ring of Generic Matrices.- 13 The Generic Division Ring of Two 2 x 2 Generic Matrices.- 14 The Center of the Generic Division Ring.- 15 Is the Center of the Generic Division Ring a Rational Function Field?.

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Book SynopsisIn July 2004, a conference on graph theory was held in Paris in memory of Claude Berge, one of the pioneers of the field. The event brought together many prominent specialists on topics such as perfect graphs and matching theory, upon which Claude Berge's work has had a major impact. This volume includes contributions to these and other topics from many of the participants.Table of ContentsClaude Berge — Sculptor of Graph Theory.- ?-path-connectivity and mk-generation: an Upper Bound on m.- Automated Results and Conjectures on Average Distance in Graphs.- Brambles, Prisms and Grids.- Dead Cell Analysis in Hex and the Shannon Game.- Ratios of Some Domination Parameters in Graphs and Claw-free Graphs.- Excessive Factorizations of Regular Graphs.- Odd Pairs of Cliques.- Recognition of Perfect Circular-arc Graphs.- On Edge-maps whose Inverse Preserves Flows or Tensions.- On the Extremal Number of Edges in 2-Factor Hamiltonian Graphs.- Generalized Colourings (Matrix Partitions) of Cographs.- A Note on [k, l]-sparse Graphs.- Even Pairs in Bull-reducible Graphs.- Kernels in Orientations of Pretransitive Orientable Graphs.- Nonrepetitive Graph Coloring.- A Characterization of the 1-well-covered Graphs with no 4-cycles.- A Graph-theoretical Generalization of Berge’s Analogue of the Erd?s-Ko-Rado Theorem.- Independence Polynomials and the Unimodality Conjecture for Very Well-covered, Quasi-regularizable, and Perfect Graphs.- Precoloring Extension on Chordal Graphs.- On the Enumeration of Bipartite Minimum Edge Colorings.- Kempe Equivalence of Colorings.- Acyclic 4-choosability of Planar Graphs with Girth at Least 5.- Automorphism Groups of Circulant Graphs — a Survey.- Hypo-matchings in Directed Graphs.- On Reed’s Conjecture about ?,? and ?.- On the Generalization of the Matroid Parity Problem.- Reconstruction of a Rank 3 Oriented Matroids from its Rank 2 Signed Circuits.- The Normal Graph Conjecture is True for Circulants.- Two-arc Transitive Near-polygonal Graphs.- Open Problems.

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Book SynopsisThe problem of enumerating maps (a map is a set of polygonal "countries" on a world of a certain topology, not necessarily the plane or the sphere) is an important problem in mathematics and physics, and it has many applications ranging from statistical physics, geometry, particle physics, telecommunications, biology, ... etc. This problem has been studied by many communities of researchers, mostly combinatorists, probabilists, and physicists. Since 1978, physicists have invented a method called "matrix models" to address that problem, and many results have been obtained.Besides, another important problem in mathematics and physics (in particular string theory), is to count Riemann surfaces. Riemann surfaces of a given topology are parametrized by a finite number of real parameters (called moduli), and the moduli space is a finite dimensional compact manifold or orbifold of complicated topology. The number of Riemann surfaces is the volume of that moduli space. More generally, an important problem in algebraic geometry is to characterize the moduli spaces, by computing not only their volumes, but also other characteristic numbers called intersection numbers.Witten's conjecture (which was first proved by Kontsevich), was the assertion that Riemann surfaces can be obtained as limits of polygonal surfaces (maps), made of a very large number of very small polygons. In other words, the number of maps in a certain limit, should give the intersection numbers of moduli spaces.In this book, we show how that limit takes place. The goal of this book is to explain the "matrix model" method, to show the main results obtained with it, and to compare it with methods used in combinatorics (bijective proofs, Tutte's equations), or algebraic geometry (Mirzakhani's recursions).The book intends to be self-contained and accessible to graduate students, and provides comprehensive proofs, several examples, and gives the general formula for the enumeration of maps on surfaces of any topology. In the end, the link with more general topics such as algebraic geometry, string theory, is discussed, and in particular a proof of the Witten-Kontsevich conjecture is provided.Trade Review“This book brings together details of topological recursion from many different papers and organizes them in an accessible way. … this book will be an invaluable resource for mathematicians learning about topological recursion.” (Daniel D. Moskovich, Mathematical Reviews, February, 2017) “The author explains how matrix models and counting surfaces are related and aims at presenting to mathematicians and physicists the random matrix approach to quantum gravity. … The book is an outstanding monograph of a recent research trend in surface theory.” (Gert Roepstorff, zbMATH 1338.81005, 2016)Table of ContentsI Maps and discrete surfaces.- II Formal matrix integrals.- III Solution of Tutte-loop equations.- IV Multicut case.- V Counting large maps.- VI Counting Riemann surfaces.- VII Topological recursion and symplectic invariants.- VIII Ising model.- Index.- Bibliography.

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Book SynopsisTrade Review"Discrete Mathematics is adequately written and well-documented.... This book presents the material on the topic in a cogently coherent manner thereby serving and justifying the purpose of writing books such as this one. The classroom-tested pedagogy and its 400 examples speak a lot about the kind and amount of sweat that must have gone into it." --zbMATH OpenTable of ContentsPart I: Logic 1. Propositional Logic 2. Predicate Logic Part II: Set Theory and Related Topics 3. Sets 4. Matrices 5. Relations 6. Functions 7. Boolean Algebra Part III: Proof Methods 8. Sequences 9. Recursion 10. Induction 11. General Proof Methods Part IV: Number Theory and Applications 12. Elementary Number Theory 13. Cryptography Part V: Probability 14. Counting Methods 15. Discrete Probability 16. Discrete Random Variables Part VI: Graph Theory 17. Graphs 18. Trees 19. Network Models Part VII: Algorithms and Finite State Machines 20. Algorithms

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Book SynopsisRandomized algorithms have become a central part of the algorithms curriculum, based on their increasingly widespread use in modern applications. This book presents a coherent and unified treatment of probabilistic techniques for obtaining high probability estimates on the performance of randomized algorithms. It covers the basic toolkit from the ChernoffâHoeffding bounds to more sophisticated techniques like martingales and isoperimetric inequalities, as well as some recent developments like Talagrand's inequality, transportation cost inequalities and log-Sobolev inequalities. Along the way, variations on the basic theme are examined, such as ChernoffâHoeffding bounds in dependent settings. The authors emphasise comparative study of the different methods, highlighting respective strengths and weaknesses in concrete example applications. The exposition is tailored to discrete settings sufficient for the analysis of algorithms, avoiding unnecessary measure-theoretic details, thus makingTrade ReviewReview of the hardback: 'It is beautifully written, contains all the major concentration results, and is a must to have on your desk.' Richard LiptonReview of the hardback: 'Concentration bounds are at the core of probabilistic analysis of algorithms. This excellent text provides a comprehensive treatment of this important subject, ranging from the very basic to the more advanced tools, including some recent developments in this area. The presentation is clear and includes numerous examples, demonstrating applications of the bounds in analysis of algorithms. This book is a valuable resource for both researchers and students in the field.' Eli Upfal, Brown UniversityReview of the hardback: 'Concentration inequalities are an essential tool for the analysis of algorithms in any probabilistic setting. There have been many recent developments on this subject, and this excellent text brings them together in a highly accessible form.' Alan Frieze, Carnegie Mellon UniversityReview of the hardback: 'The book does a superb job of describing a collection of powerful methodologies in a unified manner; what is even more striking is that basic combinatorial and probabilistic language is used in bringing out the power of such approaches. To summarize, the book has done a great job of synthesizing diverse and important material in a very accessible manner. Any student, researcher, or practitioner of computer science, electrical engineering, mathematics, operations research, and related fields, could benefit from this wonderful book. The book would also make for fruitful classes at the undergraduate and graduate levels. I highly recommend it.' Aravind Srinivasan, SIGACT NewsReview of the hardback: '… the strength of this book is that it is appropriate for both the beginner as well as the experienced researcher in the field of randomized algorithms … The exposition style […] combines informal discussion with formal definitions and proofs, giving first the intuition and motivation for the probabalistic technique at hand. … I highly recommend this book both as an advanced as well as an introductory textbook, which can also serve the needs of an experienced researcher in algorithmics.' Yannis C. Stamatiou, Mathematical ReviewsReviews of the hardback: 'This timely book brings together in a comprehensive and accessible form a sophisticated toolkit of powerful techniques for the analysis of randomized algorithms, illustrating their use with a wide array of insightful examples. This book is an invaluable resource for people venturing into this exciting field of contemporary computer science research.' Prabhakar Ragahavan, Yahoo ResearchTable of Contents1. Chernoff–Hoeffding bounds; 2. Applying the CH-bounds; 3. CH-bounds with dependencies; 4. Interlude: probabilistic recurrences; 5. Martingales and the MOBD; 6. The MOBD in action; 7. Averaged bounded difference; 8. The method of bounded variances; 9. Interlude: the infamous upper tail; 10. Isoperimetric inequalities and concentration; 11. Talagrand inequality; 12. Transportation cost and concentration; 13. Transportation cost and Talagrand's inequality; 14. Log–Sobolev inequalities; Appendix A. Summary of the most useful bounds.

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Book SynopsisEmphasizing the search for patterns within and between biological sequences, trees, and graphs, Combinatorial Pattern Matching Algorithms in Computational Biology Using Perl and R shows how combinatorial pattern matching algorithms can solve computational biology problems that arise in the analysis of genomic, transcriptomic, proteomic, metabolomic, and interactomic data. It implements the algorithms in Perl and R, two widely used scripting languages in computational biology. The book provides a well-rounded explanation of traditional issues as well as an up-to-date account of more recent developments, such as graph similarity and search. It is organized around the specific algorithmic problems that arise when dealing with structures that are commonly found in computational biology, including biological sequences, trees, and graphs. For each of these structures, the author makes a clear distinction between problems that arise in the analysis of one strTrade ReviewI like the hands-on approach this book offers, and the very pedagogical structure it follows … . The book also has tons of examples, thoughtfully chosen and beautifully laid out … the book is very well-written and accessible, undoubtedly written by an author who takes great care in preparing his manuscripts and teaching about an area he enjoys working on.—Anthony Labarre, SIGACT News, July 2012This text provides a solid foundation to the field. It will work as a practical handbook for pattern matching applications in computational biology. —Michael Goldberg, Computing Reviews, February 2010… the book makes a clear distinction between problems that emerge in the analysis of the structure and in the comparative analysis of two or more structures. … Well-known computational biology tools that allow searching nucleotide and protein databases for local sequence alignment are based on CPM algorithms only. The techniques presented in this book go beyond that. … detailed algorithm solutions in pseudocode, full Perl and R implementation, and pointers to software and implementation are presented. This … is what makes Valiente’s effort unique. …—Ernesto D’Avanzo, Computing Reviews, February 2010… It is a well-sorted collection of pattern matching algorithms that are used to work with problems in computational biology. … You can find all of the sources on the author’s website, which come in handy when you actually want to use them, since you do not have to retype them. And there is an introduction to Perl as well as to R, showing how to decode DNA/RNA-triplets to amino acids and giving some basic overview over standard functions. … I certainly recommend this as an introduction and reference to some algorithms of pattern matching in computational biology. You actually learn how algorithms over the most important data types are designed in a straightforward, logical way. …—Jannik Pewny, IACR Book Reviews, 2009…after a few minutes of random browsing, I was left with a feeling of total appreciation of the book, admiration for Prof. Gabriel Valiente, and a realization that this book will be part of my fundamental library for me and my group from the moment it is published. There are so many good things to say that I do not know where to start. The organization is straightforward with major sections that extend from simple sequences to trees to graphs. … This parallel structure makes it easy to apply lessons used on the simplest object (sequences) to objects of medium (trees) and significant (graphs) difficulty. …a wonderful way to learn leveraging … The Perl is beautifully clear and the examples have already taught me how to improve my own code.—Michael Levitt, Professor and Chair, Department of Structural Biology, Stanford University, California, USA…Balancing a careful mixture of formal methods, programming, and examples, Gabriel Valiente has managed to harmoniously bridge languages and contents into a self-contained source of lasting influence. It is not difficult to predict that this book will be studied indifferently by the specialist of biology and computer science, helping each to walk a few steps toward the other. It will entice new generations of scholars to engage in its beautiful subject.—From the Foreword, Alberto Apostolico, Professor, College of Computing, Georgia Tech, Atlanta, USAUnlocks the power for R for Perl programmers, and vice versa. Reveals R to be a powerful and accessible tool for bioinformatics. The title is a mouthful, but the use of both R and Perl for bioinformatics is revealing.—Steven Skiena, Professor, Department of Computer Science, Stony Brook University, New York, USAI like the hands-on approach this book offers, and the very pedagogical structure it follows … . The book also has tons of examples, thoughtfully chosen and beautifully laid out … the book is very well-written and accessible, undoubtedly written by an author who takes great care in preparing his manuscripts and teaching about an area he enjoys working on.—Anthony Labarre, SIGACT News, July 2012This text provides a solid foundation to the field. It will work as a practical handbook for pattern matching applications in computational biology. —Michael Goldberg, Computing Reviews, February 2010… the book makes a clear distinction between problems that emerge in the analysis of the structure and in the comparative analysis of two or more structures. … Well-known computational biology tools that allow searching nucleotide and protein databases for local sequence alignment are based on CPM algorithms only. The techniques presented in this book go beyond that. … detailed algorithm solutions in pseudocode, full Perl and R implementation, and pointers to software and implementation are presented. This … is what makes Valiente’s effort unique. …—Ernesto D’Avanzo, Computing Reviews, February 2010… It is a well-sorted collection of pattern matching algorithms that are used to work with problems in computational biology. … You can find all of the sources on the author’s website, which come in handy when you actually want to use them, since you do not have to retype them. And there is an introduction to Perl as well as to R, showing how to decode DNA/RNA-triplets to amino acids and giving some basic overview over standard functions. … I certainly recommend this as an introduction and reference to some algorithms of pattern matching in computational biology. You actually learn how algorithms over the most important data types are designed in a straightforward, logical way. …—Jannik Pewny, IACR Book Reviews, 2009…after a few minutes of random browsing, I was left with a feeling of total appreciation of the book, admiration for Prof. Gabriel Valiente, and a realization that this book will be part of my fundamental library for me and my group from the moment it is published. There are so many good things to say that I do not know where to start. The organization is straightforward with major sections that extend from simple sequences to trees to graphs. … This parallel structure makes it easy to apply lessons used on the simplest object (sequences) to objects of medium (trees) and significant (graphs) difficulty. …a wonderful way to learn leveraging … The Perl is beautifully clear and the examples have already taught me how to improve my own code.—Michael Levitt, Professor and Chair, Department of Structural Biology, Stanford University, California, USA…Balancing a careful mixture of formal methods, programming, and examples, Gabriel Valiente has managed to harmoniously bridge languages and contents into a self-contained source of lasting influence. It is not difficult to predict that this book will be studied indifferently by the specialist of biology and computer science, helping each to walk a few steps toward the other. It will entice new generations of scholars to engage in its beautiful subject.—From the Foreword, Alberto Apostolico, Professor, College of Computing, Georgia Tech, Atlanta, USAUnlocks the power for R for Perl programmers, and vice versa. Reveals R to be a powerful and accessible tool for bioinformatics. The title is a mouthful, but the use of both R and Perl for bioinformatics is revealing.—Steven Skiena, Professor, Department of Computer Science, Stony Brook University, New York, USATable of ContentsIntroduction. SEQUENCE PATTERN MATCHING: Sequences. Simple Pattern Matching in Sequences. General Pattern Matching in Sequences. TREE PATTERN MATCHING: Trees. Simple Pattern Matching in Trees. General Pattern Matching in Trees. GRAPH PATTERN MATCHING: Graphs. Simple Pattern Matching in Graphs. General Pattern Matching in Graphs. Appendices. References. Index.

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Book SynopsisSet Theoretical Aspects of Real Analysis is built around a number of questions in real analysis and classical measure theory, which are of a set theoretic flavor. Accessible to graduate students, and researchers the beginning of the book presents introductory topics on real analysis and Lebesgue measure theory. These topics highlight the boundary between fundamental concepts of measurability and nonmeasurability for point sets and functions. The remainder of the book deals with more specialized material on set theoretical real analysis. The book focuses on certain logical and set theoretical aspects of real analysis. It is expected that the first eleven chapters can be used in a course on Lebesque measure theory that highlights the fundamental concepts of measurability and non-measurability for point sets and functions. Provided in the book are problems of varying difficulty that range from simple observations to advanced results. Relatively difficult Table of ContentsZF theory and some point sets on the real line. Countable versions of AC and real analysis. Uncountable versions of AC and Lebesgue nonmeasurable sets. The Continuum Hypothesis and Lebesgue nonmeasurable sets. Measurability properties of sets and functions. Radon measures and nonmeasurable sets. Real-valued step functions with strange measurability properties. Relationships between certain classical constructions of Lebesgue nonmeasurable sets. Measurability properties of Vitali sets. A relationship between the measurability and continuity of real-valued functions. A relationship between absolutely nonmeasurable functions and Sierpinski-Zygmund functions. Sums of absolutely nonmeasurable injective functions. A large group of absolutely nonmeasurable additive functions. Additive properties of certain classes of pathological functions. Absolutely nonmeasurable homomorphisms of commutative groups. Measurable and nonmeasurable sets with homogeneous sections. A combinatorial problem on translation invariant extensions of the Lebesgue measure. Countable almost invariant partitions of G-spaces. Nonmeasurable unions of measure zero sections of plane sets. Measurability properties of well-orderings. Appendices. Bibliography. Subject Index.

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Book SynopsisThe first part of this book introduces the Schubert Cells and varieties of the general linear group Gl (k^(r+1)) over a field k according to Ehresmann geometric way. Smooth resolutions for these varieties are constructed in terms of Flag Configurations in k^(r+1) given by linear graphs called Minimal Galleries. In the second part, Schubert Schemes, the Universal Schubert Scheme and their Canonical Smooth Resolution, in terms of the incidence relation in a Tits relative building are constructed for a Reductive Group Scheme as in Grothendieck''s SGAIII. This is a topic where algebra and algebraic geometry, combinatorics, and group theory interact in unusual and deep ways.Table of ContentsGrassmannians and Flag Varieties. Schubert Cell Decomposition of Grassmannians and Flag Varieties. Resolution of Singularities of a Schubert Variety. The Singular Locus of a Schubert Variety. The Flag Complex. Configurations and Galleries Varieties. Configurations Varieties as Galleries Varieties. The Coxeter Complex. Minimal Generalized Galleries in a Coxeter Complex. Minimal Generalized Galleries in a Reductive Group Building. Parabolic Subgroups in a Reductive Group Scheme. Associated Schemes to the Relative Building. Incidence Type Schemes of the Relative Building. Smooth Resolutions of Schubert Schemes. Contracted Products and Galleries Configurations Schemes. Functoriality of Schubert Schemes Smooth Resolutions and Base Changes. About the Coxeter Complex. Generators and Relations and the Building of a Reductive Group.

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Book SynopsisA Bridge to Higher Mathematics is more than simply another book to aid the transition to advanced mathematics. The authors intend to assist students in developing a deeper understanding of mathematics and mathematical thought. The only way to understand mathematics is by doing mathematics. The reader will learn the language of axioms and theorems and will write convincing and cogent proofs using quantifiers. Students will solve many puzzles and encounter some mysteries and challenging problems. The emphasis is on proof. To progress towards mathematical maturity, it is necessary to be trained in two aspects: the ability to read and understand a proof and the ability to write a proof. The journey begins with elements of logic and techniques of proof, then with elementary set theory, relations and functions. Peano axioms for positive integers and for natural numbers follow, in particular mathematical and other forms of induction. Next Trade ReviewThis is one of the shorter books for a course that introduces students to the concept of mathematical proofs. The brevity is due to the "bare-bones" nature of the treatment. The number of topics covered, the number of examples, and the number of exercises are not smaller than what appears in competing textbooks; what is shorter is the text that one finds between theorems, lemmas, examples, and exercises. Besides the topics found in similar textbooks (i.e., proof techniques, logic, set theory, relations, and functions), there are chapters on (very) elementary number theory, combinatorial counting techniques, and Peano axioms on the set of positive integers. Several chapters are devoted to the construction of various kinds of numbers, such as integers, rationals, real numbers, and complex numbers. Answers to around half the exercises are included at the end of the book, and a few have complete solutions. This reviewer finds the book more enjoyable than the average competing textbook. --M. Bona, University of FloridaTable of ContentsElements of logicTrue and false statementsLogical connectives and truth tablesLogical equivalenceQuantifiersProofs: Structures and strategiesAxioms, theorems and proofsDirect proofContrapositive proofProof by equivalent statementsProof by casesExistence proofsProof by counterexampleProof by mathematical inductionElementary Theory of Sets. FunctionsAxioms for set theoryInclusion of setsUnion and intersection of setsComplement, difference and symmetric difference of setsOrdered pairs and the Cartersian productFunctionsDefinition and examples of functionsDirect image, inverse imageRestriction and extension of a functionOne-to-one and onto functionsComposition and inverse functions*Family of sets and the axiom of choiceRelationsGeneral relations and operations with relationsEquivalence relations and equivalence classesOrder relations*More on ordered sets and Zorn's lemmaAxiomatic theory of positive integersPeano axioms and additionThe natural order relation and subtractionMultiplication and divisibilityNatural numbersOther forms of inductionElementary number theoryAboslute value and divisibility of integersGreatest common divisor and least common multipleIntegers in base 10 and divisibility testsCardinality. Finite sets, infinite setsEquipotent setsFinite and infinite setsCountable and uncountable setsCounting techniques and combinatoricsCounting principlesPigeonhole principle and parityPermutations and combinationsRecursive sequences and recurrence relationsThe construction of integers and rationals Definition of integers and operationsOrder relation on integersDefinition of rationals, operations and orderDecimal representation of rational numbersThe construction of real and complex numbersThe Dedekind cuts approachThe Cauchy sequences approachDecimal representation of real numbersAlgebraic and transcendental numbersComples numbersThe trigonometric form of a complex number

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Book SynopsisThe book reviews inequalities for weighted entry sums of matrix powers. Applications range from mathematics and CS to pure sciences. It unifies and generalizes several results for products and powers of sesquilinear forms derived from powers of Hermitian, positive-semidefinite, as well as nonnegative matrices. It shows that some inequalities are valid only in specific cases. How to translate the Hermitian matrix results into results for alternating powers of general rectangular matrices? Inequalities that compare the powers of the row and column sums to the row and column sums of the matrix powers are refined for nonnegative matrices. Lastly, eigenvalue bounds and derive results for iterated kernels are improved.Table of ContentsIntroduction. Notation and Basic Facts. Motivation. Diagonalization and Spectral Decomposition. Undirected Graphs / Hermitian Matrices. General Results. Restricted Graph Classes. Directed Graphs / Nonsymmetric. Walks and Alternating Walks in Directed Graphs. Powers of Row and Column Sums. Applications. Bounds for the Largest Eigenvalue. Iterated Kernels. Conclusion. Bibliography. Index.

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Book SynopsisHighly technical monograph in which the authors, writing on the basis of their own recent research for the benefit of expert readers, describe a general theory of stochastic integration equations. First published in 1990.Table of ContentsIntroduction, Nonlinear Stochastic Integrators, Stochastic Calculus, Dependence on the initial Conditions and Flows.

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Book SynopsisThis book presents articles of L.V. Kantorovich on the descriptive theory of sets and function and on functional analysis in semi-ordered spaces, to demonstrate the unity of L.V. Kantorovich's creative research. It also includes two papers on the extension of Hilbert space.

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Book SynopsisDas Buch bietet einen idealen Einstieg in die Mathematik: Jedes Kapitel beginnt mit konkreten und vertrauten Begriffen oder Situationen. Davon ausgehend abstrahieren die Autoren schrittweise bis sie zu den Begriffen der modernen Mathematik kommen. Dabei wird auf Anwendungen mit einem engen Bezug zur Informatik wie etwa Routenplaner oder Codierungstheorie eingegangen. Das Buch ist so angelegt, dass jeder der drei Teile (Algebra, Analysis und Diskrete Strukturen) unabhängig voneinander gelesen und verstanden werden kann.Trade ReviewAus den Rezensionen: “Das vorliegende Buch bietet eine klassische Einführung in die für Informatiker relevante Bereiche der Mathematik: Algebra ... Analysis ... Diskrete Strukturen ... Insgesamt handelt es sich um eine nette Bereicherung der aktuellen Literatur zu diesem Thema und ich kann es nur jedem Interessierten empfehlen.“ (G. TESCHL, Monatshefte für Mathematik, October/2010, Vol. 161, Issue 3, S. 335)Table of ContentsAlgebra.- Zahlen.- Lineare Algebra.- Analysis.- Reelle Zahlen und Folgen.- Funktionen.- Diskrete Strukturen.- Diskrete Mathematik.- Grundlagen der Mathematik.

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Book SynopsisAlgebra und Diskrete Mathematik gehören zu den wichtigsten mathematischen Grundlagen der Informatik. In diese mathematischen Teilgebiete führt Band 1 des zweibändigen Lehrbuchs umfassend ein. Dabei ermöglichen klar herausgearbeitete Lösungsalgorithmen, viele Beispiele und ausführliche Beweise einen raschen Zugang zum Thema. Die umfangreiche Sammlung von Übungsaufgaben hilft bei der Erarbeitung des Stoffs und zeigt darüber hinaus, welche unterschiedlichen Anwendungsmöglichkeiten es gibt. Die 3. Auflage wurde korrigiert und erweitert.Table of ContentsTeil I Grundbegriffe der Mathematik und Algebraische Strukturen.- Teil II Lineare Algebra und analytische Geometrie.- Teil III Numerische Algebra und Kombinatorik.- Teil IV Übungsaufgaben.

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Book SynopsisA clear and lucid bottom-up approach to the basic principles of evolutionary algorithms Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies. This book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others. Evolutionary Optimization Algorithms: Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear?but theoretically rigorous?understanding of evolutionary algorithms, with an emphasis on implementation Gives a careful treatment of recently developed EAs?including opposition-based learning, artiTable of ContentsAcknowledgments xxi Acronyms xxiii List of Algorithms xxvii Part I: Introduction to Evolutionary Optimization 1 Introduction 1 2 Optimization 11 Part II: Classic Evolutionary Algorithms 3 Generic Algorithms 35 4 Mathematical Models of Genetic Algorithms 63 5 Evolutionary Programming 95 6 Evolution Strategies 117 7 Genetic Programming 141 8 Evolutionary Algorithms Variations 179 Part III: More Recent Evolutionary Algorithms 9 Simulated Annealing 223 10 Ant Colony Optimization 241 11 Particle Swarm Optimization 265 12 Differential Evolution 293 13 Estimation of Distribution Algorithms 313 14 Biogeography-Based Optimization 351 15 Cultural Algorithms 377 16 Opposition-Based Learning 397 17 Other Evolutionary Algorithms 421 Part IV: Special Type of Optimization Problems 18 Combinatorial Optimization 449 19 Constrained Optimization 481 20 Multi-Objective Optimization 517 21 Expensive, Noisy and Dynamic Fitness Functions 563 Appendices A Some Practical Advice 607 B The No Free Lunch Theorem and Performance Testing 613 C Benchmark Optimization Functions 641 References 685 Topic Index 727

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Book SynopsisTrade Review"I want to share with everybody my enjoyment of this excellent textbook."---Narciso Marti-Oliet, European Math Society"Those teaching computer scientists who take discrete mathematics alongside other mathematics modules such as linear algebra and calculus (as is the case with the CS20 students at Harvard), and who need a book with an emphasis on proof, will likely and this book a very good choice for their students."---London Mathematical Society, Glenn Hawe

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Book SynopsisUses the theory of stable marriage to introduce and illustrate a variety of important concepts and techniques of computer science and mathematics: data structures, control structures, combinatorics, probability, analysis, algebra, and especially the analysis of algorithms.Trade ReviewThis short book will provide extremely enjoyable reading to anyone with an interest in discrete mathematics and algorithm design. Mathematical Reviews Anyone would enjoy reading this book. If one had to learn French first, it would be worth the effort. Computing ReviewsTable of ContentsIntroduction, definitions, and examples Existence of a stable matching: the fundamental algorithm Principle of deferred decisions: coupon collecting Theoretical developments: application to the shortest path Searching a table by hashing; mean behavior of thefundamental algorithm Implementing the fundamental algorithm Research problems Annotated bibliography Appendix A. Later developments Appendix B. Solutions to exercises Index.

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Book SynopsisFocuses on integrable systems and symmetries presents new results on applications of symmetries and integrability techniques to the case of equations defined on the lattice. This relatively new field has many applications, for example, in describing the evolution of crystals and molecular systems defined on lattices.Table of Contents Introduction Integrability and symmetries of nonlinear differential and difference equations in two independent variables Symmetries as integrability criteria Construction of lattice equations and their Lax pair Transformation groups for quad lattice equations Algebraic entropy of the nonautonomous Boll equations Translation from Russian of R. I. Yamilov, ''On the classification of discrete eqautions'', reference [841] No quad-graph equation can have a generalized symmetry given by the narita-Itoh-Bogoyavlensky equation Bibliography Subject Index

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Book SynopsisContains a collection of mathematical applications of linear algebra, mainly in combinatorics, geometry, and algorithms. Each chapter covers a single main result with motivation and full proof, and assumes only a modest background in linear algebra. The topics include Hamming codes, the matrix-tree theorem, the Lovász bound on the Shannon capacity, and a counterexample to Borsuk's conjecture.Trade ReviewFinding examples of "linear algebra in action" that are both accessible and convincing is difficult. Thirty-three Miniatures is an attempt to present some usable examples. . . . For me, the biggest impact of the book came from noticing the tools that are used. Many linear algebra textbooks, including the one I use, delay discussion of inner products and transpose matrices till later in the course, which sometimes means they don't get discussed at all. Seeing how often the transpose matrix shows up in Matousek's miniatures made me realize space must be made for it. Similarly, the theorem relating the rank of the product of two matrices to the ranks of the factors plays a big role here. Most linear algebra instructors would benefit from this kind of insight. . . . Thirty-three Miniatures would be an excellent book for an informal seminar offered to students after their first linear algebra course. It may also be the germ of many interesting undergraduate talks. And it's fun as well." - Fernando Q. Gouvêa, MAA Reviews"[This book] is an excellent collection of clever applications of linear algebra to various areas of (primarily) discrete/combinatiorial mathematics. ... The style of exposition is very lively, with fairly standard usage of terminologies and notations. ... Highly recommended." - ChoiceTable of Contents Preface Notation Fibonacci numbers, quickly Fibonacci numbers, the formula The clubs of Oddtown Same-size intersections Error-correcting codes Odd distances Are these distances Euclidean? Packing complete bipartite graphs Equiangular lines Where is the triangle? Checking matrix multiplication Tiling a rectangle by squares Three Petersens are not enough Petersen, Hoffman–Singleton, and maybe 57 Only two distances Covering a cube minus one vertex Medium-size intersection is hard to avoid On the difficulty of reducing the diameter The end of the small coins Walking in the yard Counting spanning trees In how many ways can a man tile a board? More bricks—more walls? Perfect matchings and determinants Turning a ladder over a finite field Counting compositions Is it associative? The secret agent and umbrella Shannon capacity of the union: a tale of two fields Equilateral sets Cutting cheaply using eigenvectors Rotating the cube Set pairs and exterior products Index

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Book SynopsisTrade ReviewWritten by an eminent expert as the first monograph on this topic, this book can be recommended to anybody working on large networks and their applications in mathematics, computer science, social sciences, biology, statistical physics or chip design." - Zentralblatt Math"This is an amazing book: readable, deep, and lively. It sets out this emerging area, makes connections between old classical graph theory and graph limits, and charts the course of the future." - Persi Diaconis, Stanford University"It is always exciting when a mathematical theory turns out to be connected to a variety of other topics. This is the case with the recently developed subject of graph limits, which exhibits tight relations with a wide range of areas including statistical physics, analysis, algebra, extremal graph theory, and theoretical computer science. The book Large Networks and Graph Limits contains a comprehensive study of this active topic and an updated account of its present status. The author, Laszls Lovasz, initiated the subject, and together with his collaborators has contributed immensely to its development during the last decade. This is a beautiful volume written by an outstanding mathematician who is also an excellent expositor." - Noga Alon, Tel Aviv University, Israel"Modern combinatorics is by no means an isolated subject in mathematics, but has many rich and interesting connections to almost every area of mathematics and computer science. The research presented in Lovasz's book exemplifies this phenomenon by taking one of the most quintessentially combinatorial of objects--the finite graph--and through the process of taking limits of sequences of such graphs, reveals and clarifies connections to measure theory, analysis, statistical physics, metric geometry, spectral theory, property testing, algebraic geometry, and even Hilbert's tenth and seventeenth problems. Indeed, this book presents a wonderful opportunity for a student in combinatorics to explore other fields of mathematics, or conversely for experts in other areas of mathematics to become acquainted with some aspects of graph theory." - Terence Tao, University of California, Los Angeles, CA"László Lovász has written an admirable treatise on the exciting new theory of graph limits and graph homomorphisms, an area of great importance in the study of large networks. It is an authoritative, masterful text that reflects Lovász's position as the main architect of this rapidly developing theory. The book is a must for combinatorialists, network theorists, and theoretical computer scientists alike." - Bela Bollobas, Cambridge University, UKTable of Contents Preface Part 1. Large graphs: An informal introduction Very large networks Large graphs in mathematics and physics Part 2. The algebra of graph homomorphisms Notation and terminology Graph parameters and connection matrices Graph homomorphisms Graph algebras and homomorphism functions Part 3. Limits of dense graph sequences Kernels and graphons The cut distance Szemerédi partitions Sampling Convergence of dense graph sequences Convergence from the right On the structure of graphons The space of graphons Algorithms for large graphs and graphons Extremal theory of dense graphs Multigraphs and decorated graphs Part 4. Limits of bounded degree graphs Graphings Convergence of bounded degree graphs Right convergence of bounded degree graphs On the structure of graphings Algorithms for bounded degree graphs Part 5. Extensions: A brief survey Other combinatorial structures Appendix A Bibliography Author index Subject index Notation index

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Book SynopsisA concise yet rigorous introduction to logic and discrete mathematics. This book features a unique combination of comprehensive coverage of logic with a solid exposition of the most important fields of discrete mathematics, presenting material that has been tested and refined by the authors in university courses taught over more than a decade. The chapters on logic - propositional and first-order - provide a robust toolkit for logical reasoning, emphasizing the conceptual understanding of the language and the semantics of classical logic as well as practical applications through the easy to understand and use deductive systems of Semantic Tableaux and Resolution. The chapters on set theory, number theory, combinatorics and graph theory combine the necessary minimum of theory with numerous examples and selected applications. Written in a clear and reader-friendly style, each section ends with an extensive set of exercises, most of them provided with complete soluTrade Review"This is a very well-written brief introduction to discrete mathematics that emphasizes logic and set theory and has shorter sections on number theory, combinatorics, and graph theory." (MAA Reviews, 4 January 2016)Table of ContentsList of Boxes xiii Preface xvii Acknowledgements xxi About the Companion Website xxiii 1. Preliminaries 1 1.1 Sets 2 1.1.1 Exercises 7 1.2 Basics of logical connectives and expressions 9 1.2.1 Propositions, logical connectives, truth tables, tautologies 9 1.2.2 Individual variables and quantifiers 12 1.2.3 Exercises 15 1.3 Mathematical induction 17 1.3.1 Exercises 18 2. Sets, Relations, Orders 20 2.1 Set inclusions and equalities 21 2.1.1 Properties of the set theoretic operations 22 2.1.2 Exercises 26 2.2 Functions 28 2.2.1 Functions and their inverses 28 2.2.2 Composition of mappings 31 2.2.3 Exercises 33 2.3 Binary relations and operations on them 35 2.3.1 Binary relations 35 2.3.2 Matrix and graphical representations of relations on finite sets 38 2.3.3 Boolean operations on binary relations 39 2.3.4 Inverse and composition of relations 41 2.3.5 Exercises 42 2.4 Special binary relations 45 2.4.1 Properties of binary relations 45 2.4.2 Functions as relations 47 2.4.3 Reflexive, symmetric and transitive closures of a relation 47 2.4.4 Exercises 49 2.5 Equivalence relations and partitions 51 2.5.1 Equivalence relations 51 2.5.2 Quotient sets and partitions 53 2.5.3 The kernel equivalence of a mapping 56 2.5.4 Exercises 57 2.6 Ordered sets 59 2.6.1 Pre-orders and partial orders 59 2.6.2 Graphical representing posets: Hasse diagrams 61 2.6.3 Lower and upper bounds. Minimal and maximal elements 63 2.6.4 Well-ordered sets 65 2.6.5 Exercises 67 2.7 An introduction to cardinality 69 2.7.1 Equinumerosity and cardinality 69 2.7.2 Exercises 73 2.8 Isomorphisms of ordered sets. Ordinal numbers 75 2.8.1 Exercises 79 2.9 Application: relational databases 80 2.9.1 Exercises 86 3. Propositional Logic 89 3.1 Propositions, logical connectives, truth tables, tautologies 90 3.1.1 Propositions and propositional connectives. Truth tables 90 3.1.2 Some remarks on the meaning of the connectives 90 3.1.3 Propositional formulae 91 3.1.4 Construction and parsing tree of a propositional formula 92 3.1.5 Truth tables of propositional formulae 93 3.1.6 Tautologies 95 3.1.7 A better idea: search for a falsifying truth assignment 96 3.1.8 Exercises 97 3.2 Propositional logical consequence. Valid and invalid propositional inferences 101 3.2.1 Propositional logical consequence 101 3.2.2 Logically sound rules of propositional inference. Logically correct propositional arguments 104 3.2.3 Fallacies of the implication 106 3.2.4 Exercises 107 3.3 The concept and use of deductive systems 109 3.4 Semantic tableaux 113 3.4.1 Exercises 117 3.5 Logical equivalences. Negating propositional formulae 121 3.5.1 Logically equivalent propositional formulae 121 3.5.2 Some important equivalences 123 3.5.3 Exercises 124 3.6 Normal forms. Propositional resolution 126 3.6.1 Conjunctive and disjunctive normal forms of propositional formulae 126 3.6.2 Clausal form. Clausal resolution 129 3.6.3 Resolution-based derivations 130 3.6.4 Optimizing the method of resolution 131 3.6.5 Exercises 132 4. First-Order Logic 135 4.1 Basic concepts of first-order logic 136 4.1.1 First-order structures 136 4.1.2 First-order languages 138 4.1.3 Terms and formulae 139 4.1.4 The semantics of first-order logic: an informal outline 143 4.1.5 Translating first-order formulae to natural language 146 4.1.6 Exercises 147 4.2 The formal semantics of first–order logic 152 4.2.1 Interpretations 152 4.2.2 Variable assignment and term evaluation 153 4.2.3 Truth evaluation games 156 4.2.4 Exercises 159 4.3 The language of first-order logic: a deeper look 161 4.3.1 Translations from natural language into first-order languages 161 4.3.2 Restricted quantification 163 4.3.3 Free and bound variables. Scope of a quantifier 164 4.3.4 Renaming of a bound variable in a formula. Clean formulae 165 4.3.5 Substitution of a term for a variable in a formula. Capture of a variable 166 4.3.6 Exercises 167 4.4 Truth, logical validity, equivalence and consequence in first-order logic 171 4.4.1 More on truth of sentences in structures. Models and countermodels 171 4.4.2 Satisfiability and validity of first-order formulae 172 4.4.3 Logical equivalence in first-order logic 173 4.4.4 Some logical equivalences involving quantifiers 174 4.4.5 Negating first-order formulae 175 4.4.6 Logical consequence in first-order logic 176 4.4.7 Exercises 180 4.5 Semantic tableaux for first-order logic 185 4.5.1 Some derivations using first-order semantic tableau 186 4.5.2 Semantic tableaux for first-order logic with equality 189 4.5.3 Discussion on the quantifier rules and on termination of semantic tableaux 189 4.5.4 Exercises 191 4.6 Prenex and clausal normal forms 195 4.6.1 Prenex normal forms 195 4.6.2 Skolemization 197 4.6.3 Clausal forms 198 4.6.4 Exercises 199 4.7 Resolution in first-order logic 201 4.7.1 Propositional resolution rule in first-order logic 201 4.7.2 Substitutions of terms for variables revisited 201 4.7.3 Unification of terms 202 4.7.4 Resolution with unification in first-order logic 204 4.7.5 Examples of resolution-based derivations 205 4.7.6 Resolution for first-order logic with equality 207 4.7.7 Optimizations of the resolution method for first-order logic 207 4.7.8 Exercises 207 4.8 Applications of first-order logic to mathematical reasoning and proofs 211 4.8.1 Proof strategies: direct and indirect proofs 211 4.8.2 Tactics for logical reasoning 215 4.8.3 Exercises 216 5. Number Theory 219 5.1 The principle of mathematical induction revisited 220 5.1.1 Exercises 222 5.2 Divisibility 224 5.2.1 Basic properties of divisibility 224 5.2.2 Division with a remainder 224 5.2.3 Greatest common divisor 225 5.2.4 Exercises 227 5.3 Computing greatest common divisors. Least common multiples 230 5.3.1 Euclid’s algorithm for computing greatest common divisors 230 5.3.2 Least common multiple 232 5.3.3 Exercises 233 5.4 Prime numbers. The fundamental theorem of arithmetic 236 5.4.1 Relatively prime numbers 236 5.4.2 Prime numbers 237 5.4.3 The fundamental theorem of arithmetic 238 5.4.4 On the distribution of prime numbers 239 5.4.5 Exercises 240 5.5 Congruence relations 243 5.5.1 Exercises 246 5.6 Equivalence classes and residue systems modulo n 248 5.6.1 Equivalence relations and partitions 248 5.6.2 Equivalence classes modulo n. Modular arithmetic 249 5.6.3 Residue systems 250 5.6.4 Multiplicative inverses in ℤn 251 5.6.5 Exercises 251 5.7 Linear Diophantine equations and linear congruences 253 5.7.1 Linear Diophantine equations 253 5.7.2 Linear congruences 254 5.7.3 Exercises 256 5.8 Chinese remainder theorem 257 5.8.1 Exercises 259 5.9 Euler’s function. Theorems of Euler and Fermat 261 5.9.1 Theorems of Euler and Fermat 262 5.9.2 Exercises 264 5.10 Wilson’s theorem. Order of an integer 266 5.10.1 Wilson’s theorem 266 5.10.2 Order of an integer 266 5.10.3 Exercises 267 5.11 Application: public key cryptography 269 5.11.1 About cryptography 269 5.11.2 The idea of public key cryptography 269 5.11.3 The method RSA 270 5.11.4 Exercises 271 6. Combinatorics 274 6.1 Two basic counting principles 275 6.1.1 Exercises 281 6.2 Combinations. The binomial theorem 284 6.2.1 Counting sheep and combinations 284 6.2.2 Some important properties 286 6.2.3 Pascal’s triangle 287 6.2.4 The binomial theorem 287 6.2.5 Exercises 289 6.3 The principle of inclusion–exclusion 293 6.3.1 Exercises 296 6.4 The Pigeonhole Principle 299 6.4.3 Exercises 302 6.5 Generalized permutations, distributions and the multinomial theorem 304 6.5.1 Arranging nondistinct objects 304 6.5.2 Distributions 306 6.5.3 The multinomial theorem 308 6.5.4 Summary 310 6.5.5 Exercises 311 6.6 Selections and arrangements with repetition; distributions of identical objects 312 6.6.1 Selections with repetition 312 6.6.2 Distributions of identical objects 314 6.6.3 Arrangements with repetition 315 6.6.4 Summary 316 6.6.5 Exercises 316 6.7 Recurrence relations and their solution 318 6.7.1 Recurrence relations. Fibonacci numbers 318 6.7.2 Catalan numbers 319 6.7.3 Solving homogeneous linear recurrence relations 322 6.7.4 Exercises 327 6.8 Generating functions 329 6.8.1 Introducing generating functions 329 6.8.2 Computing coefficients of generating functions 332 6.8.3 Exercises 335 6.9 Recurrence relations and generating functions 337 6.9.1 Exercises 341 6.10 Application: classical discrete probability 343 6.10.1 Common sense probability 343 6.10.2 Sample spaces 343 6.10.3 Discrete probability 345 6.10.4 Properties of probability measures 346 6.10.5 Conditional probability and independent events 348 6.10.6 Exercises 352 7. Graph Theory 356 7.1 Introduction to graphs and digraphs 357 7.1.1 Graphs 357 7.1.2 Digraphs 364 7.1.3 Exercises 367 7.2 Incidence and adjacency matrices 370 7.2.1 Exercises 374 7.3 Weighted graphs and path algorithms 377 7.3.1 Dijkstra’s algorithm 378 7.3.2 The Floyd–Warshall algorithm 381 7.3.3 Exercises 383 7.4 Trees 385 7.4.1 Undirected trees 385 7.4.2 Computing spanning trees: Kruskal’s algorithm 388 7.4.3 Rooted trees 390 7.4.4 Traversing rooted trees 392 7.4.5 Exercises 393 7.5 Eulerian graphs and Hamiltonian graphs 395 7.5.1 Eulerian graphs and digraphs 396 7.5.2 Hamiltonian graphs and digraphs 398 7.5.3 Exercises 400 7.6 Planar graphs 404 7.6.1 Exercises 408 7.7 Graph colourings 411 7.7.1 Colourings 411 7.7.2 The four- and five-colour theorems 413 7.7.3 Exercises 414 Index 419

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Book SynopsisSolutions manual to accompanyTable of ContentsPreface vii About the Companion Website ix 1. Preliminaries 1 2. Sets, Relations, Orders 5 3. Propositional Logic 29 4. First-Order Logic 57 5. Number Theory 99 6. Combinatorics 130 7. Graph Theory 159

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Book SynopsisThis set includes Finite Mathematics: Models and Applications & Solutions Manual to accompany Finite Mathematics: Models and Applications Finite Mathematics: Models and Applications emphasizes cross-disciplinary applications that relate mathematics to everyday life. The book provides a unique combination of practical mathematical applications to illustrate the wide use of mathematics in fields ranging from business, economics, finance, management, operations research, and the life and social sciences. The book features coverage including: Algebra Skills; Mathematics of Finance; Matrix Algebra; Geometric Solutions; Simplex Methods; Application Models; Set and Probability Relationships; Random Variables and Probability Distributions; Markov Chains; Mathematical Statistics; Enrichment in Finite MathematicsTable of ContentsPreface ix About the Authors xi 1 Linear Equations and Mathematical Concepts 1 1.1 Solving Linear Equations 2 1.2 Equations of Lines and Their Graphs 7 1.3 Solving Systems of Linear Equations 15 1.4 The Numbers 𝜋 and e 21 1.5 Exponential and Logarithmic Functions 24 1.6 Variation 32 1.7 Unit Conversions and Dimensional Analysis 38 2 Mathematics of Finance 47 2.1 Simple and Compound Interest 47 2.2 Ordinary Annuity 55 2.3 Amortization 59 2.4 Arithmetic and Geometric Sequences 63 3 Matrix Algebra 71 3.1 Matrices 72 3.2 Matrix Notation, Arithmetic, and Augmented Matrices 78 3.3 Gauss–Jordan Elimination 89 3.4 Matrix Inversion and Input–Output Analysis 100 4 Linear Programming – Geometric Solutions 116 Introduction 116 4.1 Graphing Linear Inequalities 117 4.2 Graphing Systems of Linear Inequalities 121 4.3 Geometric Solutions to Linear Programs 125 5 Linear Programming – Simplex Method 136 5.1 The Standard Maximization Problem (SMP) 137 5.2 Tableaus and Pivot Operations 142 5.3 Optimal Solutions and the Simplex Method 149 5.4 Dual Programs 161 5.5 Non-SMP Linear Programs 167 6 Linear Programming – Application Models 182 7 Set and Probability Relationships 203 7.1 Sets 204 7.2 Venn Diagrams 210 7.3 Tree Diagrams 216 7.4 Combinatorics 221 7.5 Mathematical Probability 231 7.6 Bayes’ Rule and Decision Trees 245 8 Random Variables and Probability Distributions 259 8.1 Random Variables 259 8.2 Bernoulli Trials and the Binomial Distribution 265 8.3 The Hypergeometric Distribution 273 8.4 The Poisson Distribution 279 9 Markov Chains 285 9.1 Transition Matrices and Diagrams 286 9.2 Transitions 291 9.3 Regular Markov Chains 295 9.4 Absorbing Markov Chains 304 10 Mathematical Statistics 314 10.1 Graphical Descriptions of Data 315 10.2 Measures of Central Tendency and Dispersion 323 10.3 The Uniform Distribution 331 10.4 The Normal Distribution 334 10.5 Normal Distribution Applications 348 10.6 Developing and Conducting a Survey 363 11 Enrichment in Finite Mathematics 371 11.1 Game Theory 372 11.2 Applications in Finance and Economics 385 11.3 Applications in Social and Life Sciences 394 11.4 Monte Carlo Method 403 11.5 Dynamic Programming 422 Answers to Odd Numbered Exercises 439 Using Technology 502 Glossary 506 Index 513

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Book SynopsisIntroduces symbolic dynamics from a perspective of topological dynamical systems. After introducing symbolic and topological dynamics, the core of the book consists of discussions of subshifts of positive entropy, of zero entropy, other non-shift minimal action on the Cantor set, and the ergodic properties of these systems.Table of Contents First examples and general properties of subshifts Topological dynamics Subshifts of positive entropy Subshifts of zero entropy Further minimal Cantor systems Methods from ergodic theory Automata and linguistic complexity Miscellaneous background topics Solutions to exercises Bibliography Index

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Book SynopsisPresents an introductory and up-to-date course on game theory addressed to mathematicians and economists, and to other scientists having a basic mathematical background. The book is self-contained, providing a formal description of the classic game-theoretic concepts together with rigorous proofs of the main results in the field.Table of Contents Introduction to decision theory Strategic games Extensive games Games with incomplete information Fundamentals of cooperative games Applications of cooperative games Bibliography Notations Index Index of solution concepts Subject index.

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Book SynopsisDiscrete Convex Analysis is a novel paradigm for discrete optimization that combines the ideas in continuous optimization (convex analysis) and combinatorial optimization (matroid/submodular function theory) to establish a unified theoretical framework for nonlinear discrete optimization. The study of this theory is expanding with the development of efficient algorithms and applications to a number of diverse disciplines like matrix theory, operations research, and economics.This self-contained book is designed to provide a novel insight into optimization on discrete structures and should reveal unexpected links among different disciplines. It is the first and only English-language monograph on the theory and applications of discrete convex analysis.Table of Contents List of Figures Notation Preface Chapter 1: Introduction to the Central Concepts Chapter 2: Convex Functions with Combinatorial Structures Chapter 3: Convex Analysis, Linear Programming, and Integrality Chapter 4: M-Convex Sets and Submodular Set Functions Chapter 5: L-Convex Sets and Distance Functions Chapter 6: M-Convex Functions Chapter 7: L-Convex Functions Chapter 8: Conjugacy and Duality Chapter 9: Network Flows Chapter 10: Algorithms Chapter 11: Application to Mathematical Economics Chapter 12: Application to Systems Analysis by Mixed Matrices Bibliography Index.

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Book SynopsisThis book discusses the role of proofs in mathematics and computer science. In mathematics, a proof involves validating a proposition through logical deductions from axioms. Computer scientists focus on demonstrating program accuracy, given the increasing error susceptibility of software. A community of specialists aims to enhance program precision, extending to verifying computer processor chips for leading manufacturers. Creating mathematical models to affirm program validity is an active study area. A proof, in this context, involves a sequence of logical deductions from axioms and established statements, leading to the desired proposition. While crafting proofs may seem daunting, standard templates offer a framework. Some templates can be interconnected, providing both high-level structure and detailed guidance. The Principle of Mathematical Induction is applied to validate algorithms without computer reliance. Sets underpin modern mathematics and software engineering, introduced with language and typical tasks. Primary set operations' understanding enables proof techniques for functions, relations, and graphs, validating algorithms for specific tasks. The book delves into language describing element collections and sets, providing proof templates for comprehension and construction. The book covers common set operations, introduces additional proof templates, and addresses numbering elements and the Principle of Mathematical Induction. This exploration deepens the understanding of mathematical proofs and their role in computer science applications.Table of Contents Chapter 1 Mathematical Logic and Proofs Chapter 2 Basic Mathematics on the Real Numbers Chapter 3 Fundamental Mathematical Objects Chapter 4 Modular Arithmetic and Polynomials Chapter 5 Mathematical Functions Chapter 6 Linear Algebra in Mathematics Chapter 7 Mathematical Graphs Chapter 8 Mathematical Counting and Combinatorics Chapter 9 Discrete Probability in Mathematics Chapter 10 Recurrence Relations

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Book SynopsisThe primary aim of this book is to present a coherent introduction to graph theory, suitable as a textbook for advanced undergraduate and beginning graduate students in mathematics and computer science. It provides a systematic treatment of the theory of graphs without sacrificing its intuitive and aesthetic appeal. Commonly used proof techniques are described and illustrated. The book also serves as an introduction to research in graph theory.Trade Reviewdeveloped by Paul Seymour and Neil Robertson and followers), which certainly now deserves a monographic treatment of its own. Summing up: Recommended. Lower-division undergraduate through professional collections. CHOICE This book is a follow-on to the authors' 1976 text, Graphs with Applications. What began as a revision has evolved into a modern, first-class, graduate-level textbook reflecting changes in the discipline over the past thirty years... This text hits the mark by appearing in Springer’s Graduate Texts in Mathematics series, as it is a very rigorous treatment, compactly presented, with an assumption of a very complete undergraduate preparation in all of the standard topics. While the book could ably serve as a reference for many of the most important topics in graph theory, it fulfills the promise of being an effective textbook. The plentiful exercises in each subsection are divided into two groups, with the second group deemed "more challenging". Any exercises necessary for a complete understanding of the text have also been marked as such. There is plenty here to keep a graduate student busy, and any student would learn much in tackling a selection of the exercises... Not only is the content of this book exceptional, so too is its production. The high quality of its manufacture, the crisp and detailed illustrations, and the uncluttered design complement the attention to the typography and layout. Even in simple black and white with line art, it is a beautiful book. SIAM Book Reviews "A text which is designed to be usable both for a basic graph theory course … but also to be usable as an introduction to research in graph theory, by including more advanced topics in each chapter. There are a large number of exercises in the book … . The text contains drawings of many standard interesting graphs, which are listed at the end." (David B. Penman, Zentralblatt MATH, Vol. 1134 (12), 2008) MathSciNet Reviews "The present volume is intended to serve as a text for "advanced undergraduate and beginning graduate students in mathematics and computer science" (p. viii). It is well suited for this purpose. The writing is fully accessible to the stated groups of students, and indeed is not merely readable but is engaging… Even a complete listing of the chapters does not fully convey the breadth of this book… For researchers in graph theory, this book offers features which parallel the first Bondy and Murty book: it provides well-chosen terminology and notation, a multitude of especially interesting graphs, and a substantial unsolved problems section…One-hundred unsolved problems are listed in Appendix A, a treasure trove of problems worthy of study… (In short) this rewrite of a classic in graph theory stands a good chance of becoming a classic itself." "The present volume is intended to serve as a text for ‘advanced undergraduate and beginning graduate students in mathematics and computer science’ … . The writing is fully accessible to the stated groups of students, and indeed is not merely readable but is engaging. The book has many exercise sets, each containing problems … ." (Arthur M. Hobbs, Mathematical Reviews, Issue 2009 C) "A couple of fantastic features: Proof techniques: I love these nutshelled essences highlighted in bordered frames. They look like pictures on the wall and grab the view of the reader. Exercises: Their style, depth and logic remind me of Lovász’ classical exercise book. Also the fact that the name of the author is bracketed after the exercise…Figures: Extremely precise and high-tech…The book contains very recent results and ideas. It is clearly an up-to-date collection of fundamental results of graph theory…All-in-all, it is a marvelous book." (János Barát, Acta Scientiarum Mathematicarum, Vol. 75, 2009)Table of ContentsGraphs.- Subgraphs.- Connected Graphs.- Trees.- Nonseparable Graphs.- Tree-Search Algorithms.- Flows in Networks.- Complexity of Algorithms.- Connectivity.- Planar Graphs.- The Four-Colour Problem.- Stable Sets and Cliques.- The Probabilistic Method.- Vertex Colourings.- Colourings of Maps.- Matchings.- Edge Colourings.- Hamilton Cycles.- Coverings and Packings in Directed Graphs.- Electrical Networks.- Integer Flows and Coverings.

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Book SynopsisThis practically-oriented textbook presents an accessible introduction to discrete mathematics through a substantial collection of classroom-tested exercises. Each chapter opens with concise coverage of the theory underlying the topic, reviewing the basic concepts and establishing the terminology, as well as providing the key formulae and instructions on their use. This is then followed by a detailed account of the most common problems in the area, before the reader is invited to practice solving such problems for themselves through a varied series of questions and assignments.Topics and features: provides an extensive set of exercises and examples of varying levels of complexity, suitable for both laboratory practical training and self-study; offers detailed solutions to many problems, applying commonly-used methods and computational schemes; introduces the fundamentals of mathematical logic, the theory of algorithms, Boolean algebra, graph theory, sets, relations, functions, and combinatorics; presents more advanced material on the design and analysis of algorithms, including asymptotic analysis, and parallel algorithms; includes reference lists of trigonometric and finite summation formulae in an appendix, together with basic rules for differential and integral calculus.This hands-on study guide is designed to address the core needs of undergraduate students training in computer science, informatics, and electronic engineering, emphasizing the skills required to develop and implement an algorithm in a specific programming language.Table of ContentsFundamentals of Mathematical Logic Set Theory Relations and Functions Combinatorics Graphs Boolean Algebra Complex Numbers Recurrence Relations Concept of an Algorithm, Correctness of Algorithms Turing Machine Asymptotic Analysis Basic Algorithms Parallel Algorithms

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Book SynopsisContinuing the theme of the previous volumes, these seminar notes reflect general trends in the study of Geometric Aspects of Functional Analysis, understood in a broad sense. Two classical topics represented are the Concentration of Measure Phenomenon in the Local Theory of Banach Spaces, which has recently had triumphs in Random Matrix Theory, and the Central Limit Theorem, one of the earliest examples of regularity and order in high dimensions. Central to the text is the study of the Poincaré and log-Sobolev functional inequalities, their reverses, and other inequalities, in which a crucial role is often played by convexity assumptions such as Log-Concavity. The concept and properties of Entropy form an important subject, with Bourgain's slicing problem and its variants drawing much attention. Constructions related to Convexity Theory are proposed and revisited, as well as inequalities that go beyond the Brunn–Minkowski theory. One of the major current research directions addressed is the identification of lower-dimensional structures with remarkable properties in rather arbitrary high-dimensional objects. In addition to functional analytic results, connections to Computer Science and to Differential Geometry are also discussed. Table of Contents- Jean Bourgain: In Memoriam. - A Generalized Central Limit Conjecture for Convex Bodies. - The Lower Bound for Koldobsky’s Slicing Inequality via Random Rounding. - Two-Sided Estimates for Order Statistics of Log-Concave Random Vectors. - Further Investigations of Rényi Entropy Power Inequalities and an Entropic Characterization of s-Concave Densities. - Small Ball Probability for the Condition Number of Random Matrices. - Concentration of the Intrinsic Volumes of a Convex Body. - Two Remarks on Generalized Entropy Power Inequalities. - On the Geometry of Random Polytopes. - Reciprocals and Flowers in Convexity. - Moments of the Distance Between Independent Random Vectors. - The Alon–Milman Theorem for Non-symmetric Bodies. - An Interpolation Proof of Ehrhard’s Inequality. - Bounds on Dimension Reduction in the Nuclear Norm. - High-Dimensional Convex Sets Arising in Algebraic Geometry. - Polylog Dimensional Subspaces of lN/∞. - On a Formula for the Volume of Polytopes.

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Book SynopsisIn the present era dominated by computers, graph theory has come into its own as an area of mathematics, prominent for both its theory and its applications. One of the richest and most studied types of graph structures is that of the line graph, where the focus is more on the edges of a graph than on the vertices. A subject worthy of exploration in itself, line graphs are closely connected to other areas of mathematics and computer science. This book is unique in its extensive coverage of many areas of graph theory applicable to line graphs. The book has three parts. Part I covers line graphs and their properties, while Part II looks at features that apply specifically to directed graphs, and Part III presents generalizations and variations of both line graphs and line digraphs.Line Graphs and Line Digraphs is the first comprehensive monograph on the topic. With minimal prerequisites, the book is accessible to most mathematicians and computer scientists who have had an introduction graph theory, and will be a valuable reference for researchers working in graph theory and related fields.Table of ContentsPart I Line Graphs.- 1 Fundamentals of Line Graphs.- 2 Line Graph Isomorphisms.- 3 Characterization of Line Graphs.- 4 Spectral Properties of Line Graphs.- 5 Planarity of Line Graphs.- 6 Connectivity of Line Graphs.- 7 Tranversability in Line Graphs.- 8 Colorability in Line Graphs.- 9 Distance and Transitivity in Line Graphs.- Part II Line Digraphs.- 10 Fundamentals of Line Digraphs.- 11 Characterizations of Line Digraphs.- 12 Iterated Line Digraphs.- Part III Generalizations.- 13 Total Graphs and Total Digraphs.- 14 Path Graphs and Path Digraphs.- 15 Super Line Graphs and Super Line Digraphs.- 16 Line Graphs of Signed Graphs.- 17 The Krausz Dimension of Graph.- Reference. Index of Names.- Index of Definitions.

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This textbook discusses the design and implementation of basic algebraic graph algorithms, and algebraic graph algorithms for complex networks, employing matroids whenever possible. The text describes the design of a simple parallel matrix algorithm kernel that can be used for parallel processing of algebraic graph algorithms. Example code is presented in pseudocode, together with case studies in Python and MPI. The text assumes readers have a background in graph theory and/or graph algorithms.

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