Maths for computer scientists Books
Springer New York Combinatorial Computational Biology of RNA Pseudoknots and Neutral Networks
Book SynopsisIn this monograph, new combinatorial and computational approaches in the study of RNA structures are presented which enhance both mathematics and computational biology.Trade ReviewFrom the reviews:“This book is devoted to the study of the structure of combinatorial models of the ribonucleic acid (RNA). … This book can serve as an introduction to the study of combinatorial computational biology as well as a reference of known results and state of the art in this topic.” (Ludovit Niepel, Zentralblatt MATH, Vol. 1207, 2011)Table of ContentsIntroduction.- Secondary Structures, Pseudoknot RNA and Beyond.- Folding Sequences into Structures.- Evolution of RNA Sequences.- Methods.- References.- Index.
£49.49
Springer Explorations in Monte Carlo Methods
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£44.99
Springer Counting The Art of Enumerative Combinatorics
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£66.49
Springer Neural and Automata Networks Dynamical Behavior and Applications 58 Mathematics and Its Applications
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£87.78
Springer Automated Development of Fundamental Mathematical Theories 2 Automated Reasoning Series
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£170.99
Springer Algebras and Orders Proceedings of the NATO Advanced Study Institute and Seminaire De Mathematiques Superieures Montreal Canada July 29August 9 1991 389 Nato Science Series C
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£427.49
Springer Finite and Infinite Combinatorics in Sets and Logic Proceedings of the NATO Advanced Study Institute Banff Alberta Canada April 21May 4 1992 411 Nato Science Series C
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£237.49
Springer Universal Compression and Retrieval 274 Mathematics and Its Applications
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£123.49
Springer Cellular Automata Dynamical Systems and Neural Networks 282 Mathematics and Its Applications
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£85.49
Springer Graph Theoretical Approaches to Chemical Reactivity 9 Understanding Chemical Reactivity
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£123.49
Springer Inconsistent Mathematics 312 Mathematics and Its Applications
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£44.99
Springer Discrete Analysis and Operations Research 355 Mathematics and Its Applications
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£85.49
Springer Resolution Proof Systems An Algebraic Theory 4 Automated Reasoning Series
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£85.49
Springer Problems and Exercises in Discrete Mathematics 14 Texts in the Mathematical Sciences
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£104.49
Springer Operations Research and Discrete Analysis 391 Mathematics and Its Applications
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£85.49
Springer Graph Symmetry Algebraic Methods and Applications 497 Nato Science Series C
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£170.99
Springer Exercises in Graph Theory 19 Texts in the Mathematical Sciences
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£189.99
Springer Applications of Fibonacci Numbers Volume 7
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£85.49
Springer Automated Deduction A Basis for Applications Volume I Foundations Calculi and Methods Volume II Systems and Implementation Techniques Volume III Applications
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£170.99
Springer Enumerative Theory Of Maps 468 Mathematics and Its Applications
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£85.49
Springer Global Analysis in Linear Differential Equations 471 Mathematics and Its Applications
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£85.49
Springer Semirings and their Applications
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£104.49
Springer Power Algebras over Semirings With Applications in Mathematics and Computer Science 488 Mathematics and Its Applications
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£104.49
Springer Difference Sets Sequences and their Correlation Properties Proceedings of the NATO Advanced Study Institute on Difference Sets Sequence and Their August 1998 542 Nato Science Series C
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£170.99
Springer Difference Sets Sequences and Their Correlation Properties Proceedings of the NATO Advanced Study Institute on Difference Sets Sequence and Their August 1998 542 Nato Science Series C
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£170.99
Springer NearRings and NearFields Proceedings of the Conference on NearRings and NearFields Stellenbosch South Africa July 916 1997
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£44.99
Springer Mathematical Foundations of Information Retrieval
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£44.99
Springer Practical Asymptotics
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£85.49
Springer Theory and Applications of HigherDimensional Hadamard Matrices 1 Combinatorics and Computer Science
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£44.99
Springer Us NonFunctional Requirements in Software Engineering 5 International Series in Software Engineering
Book SynopsisDetailed treatments of particular NFRs - accuracy, security and performance requirements - along with treatments of NFRs for information systems are presented as specializations of the NFR Framework.Table of ContentsList of Figures. List of Tables. Legend for Figures. Preface. 1. Introduction. Part I: The NFR Framework. 2. The NFR Framework in Action. 3. Softgoal Interdependency Graphs. 4. Cataloguing Refinement Methods and Correlations. Part II: Types of Non-Functional Requirements. 5. Types of NFRs. 6. Accuracy Requirements. 7. Security Requirements. 8. Performance Requirements. 9. Performance Requirements for Information Systems. Part III. Case Studies and Applications. 10. Introduction to the Studies and Applications. 11. A Credit Card System. 12. An Administrative System. 13. Application to Software Architecture. 14. Enterprise Modelling and Business Process Redesign. 15. Assessment of Studies. Postscript. Bibliography.
£474.99
Springer Conditional Monte Carlo
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£197.99
Springer DemandDriven Associative Classification
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£53.17
Springer-Verlag New York Inc. Monte Carlo Statistical Methods
Book SynopsisWe have sold 4300 copies worldwide of the first edition (1999). This new edition contains five completely new chapters covering new developments. Trade ReviewFrom the reviews: MATHEMATICAL REVIEWS "Although the book is written as a textbook, with many carefully worked out examples and exercises, it will be very useful for the researcher since the authors discuss their favorite research topics (Monte Carlo optimization and convergence diagnostics) going through many relevant references…This book is a comprehensive treatment of the subject and will be an essential reference for statisticians working with McMC." From the reviews of the second edition: "Only 2 years after its first edition this carefully revised second edition accounts for the rapid development in this field...This book can be highly recommended for students and researchers interested in learning more about MCMC methods and their background." Biometrics, March 2005 "This is a comprehensive book for advanced graduate study by statisticians." Technometrics, May 2005 "This excellent text is highly recommended..." Short Book Reviews of the ISI, April 2005 "This book provides a thorough introduction to Monte Carlo methods in statistics with an emphasis on Markov chain Monte Carlo methods. … Each chapter is concluded by problems and notes. … The book is self-contained and does not assume prior knowledge of simulation or Markov chains. …. on the whole it is a readable book with lots of useful information." (Søren Feodor Nielsen, Journal of Applied Statistics, Vol. 32 (6), August, 2005) "This revision of the influential 1999 text … includes changes to the presentation in the early chapters and much new material related to MCMC and Gibbs sampling. The result is a useful introduction to Monte Carlo methods and a convenient reference for much of current methodology. … The numerous problems include many with analytical components. The result is a very useful resource for anyone wanting to understand Monte Carlo procedures. This excellent text is highly recommended … ." (D.F. Andrews, Short Book Reviews, Vol. 25 (1), 2005) "You have to practice statistics on a desert island not to know that Markov chain Monte Carlo (MCMC) methods are hot. That situation has caused the authors not only to produce a new edition of their landmark book but also to completely revise and considerably expand it. … This is a comprehensive book for advanced graduate study by statisticians." (Technometrics, Vol. 47 (2), May, 2005) "This remarkable book presents a broad and deep coverage of the subject. … This second edition is a considerably enlarged version of the first. Some subjects that have matured more rapidly in the five years following the first edition, like reversible jump processes, sequential MC, two-stage Gibbs sampling and perfect sampling have now chapters of their own. … the book is also very well suited for self-study and is also a valuable reference for any statistician who wants to study and apply these techniques." (Ricardo Maronna, Statistical Papers, Vol. 48, 2006) "This second edition of ‘Monte Carlo Statistical Methods’ has appeared only five years after the first … the new edition aims to incorporate recent developments. … Each chapter includes sections with problems and notes. … The style of the presentation and many carefully designed examples make the book very readable and easily accessible. It represents a comprehensive account of the topic containing valuable material for lecture courses as well as for research in this area." (Evelyn Buckwar, Zentrablatt MATH, Vol. 1096 (22), 2006) "This is a useful and utilitarian book. It provides a catalogue of modern Monte carlo based computational techniques with ultimate emphasis on Markov chain Monte Carlo (MCMC) … . an excellent reference for anyone who is interested in algorithms for various modes of Markov chain (MC) methodology … . a must for any researcher who believes in the importance of understanding what goes on inside of the MCMC ‘black box.’ … I recommend the book to all who wish to learn about statistical simulation." (Wesley O. Johnson, Journal of the American Statistical Association, Vol. 104 (485), March, 2009)Table of ContentsIntroduction * Random Variable Generation * Monte Carlo Integration * Controlling Monte Carlo Variance * Monte Carlo Optimization * Markov Chains * The Metropolis-Hastings Algorithm * The Slice Sampler * The Two-Stage Gibbs Sampler * The Multi-Stage Gibbs Sampler * Variable Dimension Models and Reversible Jump * Diagnosing Convergence * Perfect Sampling * Iterated and Sequential Importance Sampling
£104.49
Springer New York Nonparametric Functional Data Analysis Theory and Practice Springer Series in Statistics
Book SynopsisAt the same time it shows how functional data can be studied through parameter-free statistical ideas, and offers an original presentation of new nonparametric statistical methods for functional data analysis.Trade ReviewFrom the reviews: "This is certainly a very valuable book for anyone interested in this new methodology." N.D.C. Veraverbeke for Short Book Reviews of the ISI, December 2006 "The present book does bring something new and, indeed some novel theoretical investigations into the kinds of functional data problems … . I do think the present book is a worthy contribution to the literature. The authors have done a nice job of summarizing some of ongoing research … . Researchers in the growing functional statistics community should be glad to have a copy of the book." (Z. Q. John Lu, Technometrics, Vol. 49 (2), 2007) "This book presents new nonparametric staustical methods for samples of functional data … . The computational aspects of the book are oriented toward practitioners whereas open problems emerging from this new field of statistics will attract Ph. D. students and academic researchers. This book is also accessible to graduate students starting out in the area of functional statistics." (Fazil A. Aliev, Mathematical Reviews, Issue 2007 b) "Nonparametric Functional Data Analysis explores nonparametric methods as that can be applied to functional data, developing new methods and providing theoretical results for the conditional and unconditional mean, median, and mode for independent and dependent functional data. … As a resource for those interested in FDA research and methods, it is highly recommended. … This book should spur new and exciting research in FDA, and it provides new tools that are ready for application to real data sets." (Mark Greenwood, Journal of the American Statistical Association, Vol. 102 (479), 2007) "Example data sets that motivate the development of the models are also provided. … The index provided seems to be fairly complete and is helpful in looking up topics discusses in this monograph. Several chapters end in a section in which the authors provide additional comments, discussions and pose some open problems in this area, which should be appealing for researchers in this field. … This book should be useful for all people interested in the area of functional data analysis." (Anatolij Dvurecenskij, Zentralblatt MATH, Vol. 1119 (21), 2007)Table of ContentsIntroduction to functional nonparametric statistics.- Some functional datasets and associated statistical problematics.- What is a well adapted space for functional data?.- Local weighting of functional variables.- Functional nonparametric prediction methodologies.- Some selected asymptotics.- Computational issues.- Nonparametric supervised classification for functional data.- Nonparametric unsupervised classification for functional data.- Mixing, nonparametric and functional statistics.- Some selected asymptotics.- Application to continuous time processes prediction.- Small ball probabilities, semi-metric spaces and nonparametric statistics.- Conclusion and perspectives.
£104.99
Springer New York Bayesian Networks and Influence Diagrams A Guide to Construction and Analysis 22 Information Science and Statistics
Book SynopsisThe techniques and methods presented for knowledge elicitation, model construction and verification, modeling techniques and tricks, learning models from data, and analyses of models have all been developed and refined on the basis of numerous courses that the authors have held for practitioners worldwide.Trade ReviewFrom the book reviews:“The monograph concentrates on intelligent systems for decision support based on probabilistic models, including Bayesian networks and influence diagrams. … This monograph provides a review of recent state affairs of probabilistic networks that can be useful for professionals, practitioners, and researchers from diverse fields of statistics and related disciplines. I think it can be used as a textbook in its own right for an upper level undergraduate course, especially for a reading course.” (Technometrics, Vol. 55 (2), May, 2013)Table of ContentsIntroduction.- Networks.- Probabilities.- Probabilistic Networks.- Solving Probabilistic Networks.- Eliciting the Model.- Modeling Techniques.- Data-Driven Modeling.- Conflict Analysis.- Sensitivity Analysis.- Value of Information Analysis.- Quick Reference to Model Construction.- List of Examples.- List of Figures.- List of Tables.- List of Symbols.- References.- Index.
£82.49
Apress Metaprogramming in R
Table of Contents1. Anatomy of a Function2. Inside a Function-Call3. Expressions and Environments4. Manipulating Expressions 5. Working with Substitutions
£35.99
Springer New York Bayesian Networks and Influence Diagrams A Guide to Construction and Analysis
Book SynopsisThe techniques and methods presented for knowledge elicitation, model construction and verification, modeling techniques and tricks, learning models from data, and analyses of models have all been developed and refined on the basis of numerous courses that the authors have held for practitioners worldwide.Trade ReviewFrom the book reviews:“The monograph concentrates on intelligent systems for decision support based on probabilistic models, including Bayesian networks and influence diagrams. … This monograph provides a review of recent state affairs of probabilistic networks that can be useful for professionals, practitioners, and researchers from diverse fields of statistics and related disciplines. I think it can be used as a textbook in its own right for an upper level undergraduate course, especially for a reading course.” (Technometrics, Vol. 55 (2), May, 2013)Table of ContentsIntroduction.- Networks.- Probabilities.- Probabilistic Networks.- Solving Probabilistic Networks.- Eliciting the Model.- Modeling Techniques.- Data-Driven Modeling.- Conflict Analysis.- Sensitivity Analysis.- Value of Information Analysis.- Quick Reference to Model Construction.- List of Examples.- List of Figures.- List of Tables.- List of Symbols.- References.- Index.
£59.99
Springer London Ltd A First Course in Discrete Mathematics
Book SynopsisDrawing on many years'experience of teaching discrete mathem atics to students of all levels, Anderson introduces such as pects as enumeration, graph theory and configurations or arr angements. Starting with an introduction to counting and rel ated problems, he moves on to the basic ideas of graph theor y with particular emphasis on trees and planar graphs. He de scribes the inclusion-exclusion principle followed by partit ions of sets which in turn leads to a study of Stirling and Bell numbers. Then follows a treatment of Hamiltonian cycles, Eulerian circuits in graphs, and Latin squares as well as proof of Hall's theorem. He concludes with the constructions of schedules and a brief introduction to block designs. Each chapter is backed by a number of examples, with straightforw ard applications of ideas and more challenging problems.Trade Review"Wie der Titel andeutet, handelt es sich bei diesem Buch um eine elementare Einführung in Denkweisen und Methoden der Diskreten Mathematik. Die fachlichen Voraussetzungen an den Leser sind minimal. Darauf aufbauend wird ein doch recht buntes Bild entwickelt, bestehend vor allem aus den wichtigsten Konzepten aus Kombinatorik und Graphentheorie sowie einigen spezielleren Themen wie Designs und Codes.... Der Vorteil besteht darin, dass auch dem mathematischen Laien auf knapp 200 Seiten ein durchaus einprägsames Bild von einem Zweig der Mathematik vermittelt wird, der in unserer Zeit u.a. durch die Allgegenwart der sogenannten Informationstechnologie extrem an Bedeutung gewonnen hat."Internationale Mathematische Nachrichten, Nr. 187, August 2001Table of Contents1. Counting and Binomial Coefficients.- 2. Recurrence.- 3. Introduction to Graphs.- 4. Travelling Round a Graph.- 5. Partitions and Colourings.- 6. The Inclusion Exclusion Principle.- 7. Latin Squares and Hall’s Theorem.- 8. Schedules and 1-Factorisations.- 9. Introduction to Designs.- Solutions.- Further Reading.
£29.99
Springer Nature Switzerland AG Mathematical Foundations of Advanced Informatics: Volume 1: Inductive Approaches
Book SynopsisThe books in this trilogy capture the foundational core of advanced informatics. The authors make the foundations accessible, enabling students to become effective problem solvers.This first volume establishes the inductive approach as a fundamental principle for system and domain analysis. After a brief introduction to the elementary mathematical structures, such as sets, propositional logic, relations, and functions, the authors focus on the separation between syntax (representation) and semantics (meaning), and on the advantages of the consistent and persistent use of inductive definitions. They identify compositionality as a feature that not only acts as a foundation for algebraic proofs but also as a key for more general scalability of modeling and analysis. A core principle throughout is invariance, which the authors consider a key for the mastery of change, whether in the form of extensions, transformations, or abstractions.This textbook is suitable for undergraduate and graduate courses in computer science and for self-study. Most chapters contain exercises and the content has been class-tested over many years in various universities.Table of ContentsIntroduction.- Propositions and Sets.- Relations and Functions.- Inductive Definitions.- Inductive Proofs.- Inductive Approach: Potential, Limitations, and Pragmatics.
£27.99
Springer Nature Switzerland AG Graph Drawing and Network Visualization: 27th
Book SynopsisThis book constitutes the refereed proceedings of the 27th International Symposium on Graph Drawing and Network Visualization, GD 2019, held in Prague, Czech Republic, in September 2019.The 42 papers and 12 posters presented in this volume were carefully reviewed and selected from 113 submissions. They were organized into the following topical sections: Cartograms and Intersection Graphs, Geometric Graph Theory, Clustering, Quality Metrics, Arrangements, A Low Number of Crossings, Best Paper in Track 1, Morphing and Planarity, Parameterized Complexity, Collinearities, Topological Graph Theory, Best Paper in Track 2, Level Planarity, Graph Drawing Contest Report, and Poster Abstracts.Table of ContentsCartograms and Intersection Graphs.- Stick Graphs with Length Constraints.- Representing Graphs and Hypergraphs by Touching Polygons in 3D.- Optimal Morphs of Planar Orthogonal Drawings II.- Computing Stable Demers Cartograms.- Geometric Graph Theory.- Bundled Crossings Revisited.- Crossing Numbers of Beyond-Planar Graphs.- On the 2-Colored Crossing Number.- Minimal Representations of Order Types by Geometric Graphs.- Balanced Schnyder woods for planar triangulations: an experimental study with applications to graph drawing and graph separators.- Clustering.- A Quality Metric for Visualization of Clusters in Graphs.- Multi-level Graph Drawing using Infomap Clustering.- On Strict (Outer-)Confluent Graphs.- Quality Metrics.- On the Edge-Length Ratio of Planar Graphs.- Node Overlap Removal Algorithms: A Comparative Study.- Graphs with large total angular resolution.- Arrangements.- Computing Height-Optimal Tangles Faster.- On Arrangements of Orthogonal Circles.- Extending Simple Drawings.- Coloring Hasse diagrams and disjointness graphs of curves.- A Low Number of Crossings.- Efficient Generation of Different Topological Representations of Graphs Beyond-Planarity.- The QuaSEFE Problem.- ChordLink: A New Hybrid Visualization Model.- Stress-Plus-X (SPX) Graph Layout.- Best Paper in Track 1.- Exact Crossing Number Parameterized by Vertex Cover.- Morphing and Planarity.- Maximizing Ink in Partial Edge Drawings of k-Plane Graphs.- Graph Drawing with Morphing Partial Edges.- A Note on Universal Point Sets for Planar Graphs.- Parameterized Complexity.- Parameterized Algorithms for Book Embedding Problems.- Sketched Representations and Orthogonal Planarity of Bounded Treewidth Graphs.- Collinearities.- 4-Connected Triangulations on Few Lines.- Line and Plane Cover Numbers Revisited.- Drawing planar graphs with few segments on a polynomial grid.- Variants of the Segment Number of a Graph.- Topological Graph Theory.- Local and Union Page Numbers.- Mixed Linear Layouts: Complexity, Heuristics, and Experiments.- Homotopy height, grid-major height and graph-drawing height.- On the Edge-Vertex Ratio of Maximal Thrackles.- Best Paper in Track 2.- Symmetry Detection and Classification in Drawings of Graphs.- Level Planarity.- An SPQR-Tree-Like Embedding Representation for Upward Planarity.- A Natural Quadratic Approach to the Generalized Graph Layering Problem.- Graph Stories in Small Area.- Level-Planar Drawings with Few Slopes.- Graph Drawing Contest Report.- Graph Drawing Contest Report.- Poster Abstracts.- A 1-planarity Testing and Embedding Algorithm.- Stretching Two Pseudolines in Planar Straight-Line Drawings.- Adventures in Abstraction: Reachability in Hierarchical Drawings.- On Topological Book Embedding for k-Plane Graphs.- On Compact RAC Drawings.- FPQ-choosable Planarity Testing.- Packing Trees into 1-Planar Graphs.- Geographic Network Visualization Techniques: A Work-In-Progress Taxonomy.- On the Simple Quasi Crossing Number of K 11.- Minimising Crossings in a Tree-Based Network.- Crossing Families and Their Generalizations.- Which Sets of Strings are Pseudospherical?.
£44.99
Springer Nature Switzerland AG Sets, Logic and Maths for Computing
Book SynopsisThis easy-to-understand textbook introduces the mathematical language and problem-solving tools essential to anyone wishing to enter the world of computer and information sciences. Specifically designed for the student who is intimidated by mathematics, the book offers a concise treatment in an engaging style.The thoroughly revised third edition features a new chapter on relevance-sensitivity in logical reasoning and many additional explanations on points that students find puzzling, including the rationale for various shorthand ways of speaking and ‘abuses of language’ that are convenient but can give rise to misunderstandings. Solutions are now also provided for all exercises.Topics and features: presents an intuitive approach, emphasizing how finite mathematics supplies a valuable language for thinking about computation; discusses sets and the mathematical objects built with them, such as relations and functions, as well as recursion and induction; introduces core topics of mathematics, including combinatorics and finite probability, along with the structures known as trees; examines propositional and quantificational logic, how to build complex proofs from simple ones, and how to ensure relevance in logic; addresses questions that students find puzzling but may have difficulty articulating, through entertaining conversations between Alice and the Mad Hatter; provides an extensive set of solved exercises throughout the text.This clearly-written textbook offers invaluable guidance to students beginning an undergraduate degree in computer science. The coverage is also suitable for courses on formal methods offered to those studying mathematics, philosophy, linguistics, economics, and political science. Assuming only minimal mathematical background, it is ideal for both the classroom and independent study.Table of ContentsPart I: Sets Collecting Things Together: Sets Comparing Things: Relations Associating One Item with Another: Functions Recycling Outputs as Inputs: Induction and Recursion Part II: Math Counting Things: Combinatorics Weighing the Odds: Probability Squirrel Math: Trees Part III: Logic Yea and Nay: Propositional Logic Something about Everything: Quantificational Logic Just Supposing: Proof and Consequence Sticking to the Point: Relevance in Logic
£22.99
Springer Nature Switzerland AG Audit Analytics: Data Science for the Accounting
Book SynopsisToday, information technology plays a pivotal role in financial control and audit: most financial data is now digitally recorded and dispersed among servers, clouds and networks over which the audited firm has no control. Additionally, a firm’s data—particularly in the case of finance, software, insurance and biotech firms— comprises most of the audited value of the firm. Financial audits are critical mechanisms for ensuring the integrity of information systems and the reporting of organizational finances. They help avoid the abuses that led to passage of legislation such as the Foreign Corrupt Practices Act (1977), and the Sarbanes-Oxley Act (2002). Audit effectiveness has declined over the past two decades as auditor skillsets have failed to keep up with advances in information technology. Information and communication technology lie at the core of commerce today and are integrated in business processes around the world. This book is designed to meet the increasing need of audit professionals to understand information technology and the controls required to manage it. The material included focuses on the requirements for annual Securities and Exchange Commission audits (10-K) for listed corporations. These represent the benchmark auditing procedures for specialized audits, such as internal, governmental, and attestation audits.Using R and RStudio, the book demonstrates how to render an audit opinion that is legally and statistically defensible; analyze, extract, and manipulate accounting data; build a risk assessment matrix to inform the conduct of a cost-effective audit program; and more.Table of Contents1. Fundamentals of Auditing Financial Statements.- 2. Foundations of Audit Analytics.- 3. Analysis of Accounting Transactions.- 4. Risk Assessment and Planning.- 5. Analytical Review: Technical Analysis.- 6. Analytical Review: Intelligence Scanning.- 7. Design of Audit Programs.- 8. Interim Compliance Tests.- 9. Substantive Tests.- 10. Sarbanes-Oxley Engagements.- 11. Blockchains, Cybercrime and Forensics.- 12. Special Engagements: Forecasts and Valuation.- 13. Simulated Transactions for Auditing Service Organizations.
£59.99
Springer Nature Switzerland AG Discrete Mathematics and Graph Theory: A Concise
Book SynopsisThis textbook can serve as a comprehensive manual of discrete mathematics and graph theory for non-Computer Science majors; as a reference and study aid for professionals and researchers who have not taken any discrete math course before. It can also be used as a reference book for a course on Discrete Mathematics in Computer Science or Mathematics curricula. The study of discrete mathematics is one of the first courses on curricula in various disciplines such as Computer Science, Mathematics and Engineering education practices. Graphs are key data structures used to represent networks, chemical structures, games etc. and are increasingly used more in various applications such as bioinformatics and the Internet. Graph theory has gone through an unprecedented growth in the last few decades both in terms of theory and implementations; hence it deserves a thorough treatment which is not adequately found in any other contemporary books on discrete mathematics, whereas about 40% of this textbook is devoted to graph theory. The text follows an algorithmic approach for discrete mathematics and graph problems where applicable, to reinforce learning and to show how to implement the concepts in real-world applications.Trade Review“This accessible reference book should be well received by undergraduate-level CS, engineering, and mathematics students.” (Soubhik Chakraborty, Computing Reviews, July 12, 2022)“The book under review is an elementary introduction to mathematical logic, set theory, discrete mathematics, number theory, probability theory and graph theory. Its undoubted advantage is its good algorithmic support. … I would recommend this book to students studying computer science at the bachelor’s level.” (I. M. Erusalimskiy, zbMATH 1477.68004, 2022)Table of ContentsPreface.- Part I: Fundamentals of Discrete Mathematics.- Logic.- Proofs.- Algorithms.- Set Theory.- Relations and Functions.- Sequences, Induction and Recursion.- Introduction to Number Theory.- Counting and Probability.- Boolean Algebra and Combinational Circuits.- Introduction to the Theory of Computation.- Part II: Graph Theory.- Introduction to Graphs.- Trees and Traversals.- Subgraphs.- Connectivity, Network Flows and Shortest Paths.- Graph Applications.- A:.- Pseudocode Conventions.- Index.
£21.53
Springer Nature Switzerland AG Algebra and Geometry with Python
Book SynopsisThis book teaches algebra and geometry. The authors dedicate chapters to the key issues of matrices, linear equations, matrix algorithms, vector spaces, lines, planes, second-order curves, and elliptic curves. The text is supported throughout with problems, and the authors have included source code in Python in the book. The book is suitable for advanced undergraduate and graduate students in computer science. Trade Review“It is most interesting to combine a classical mathematical topic with a new evolving programming language and exactly this is obtained by this book. … This material is used as a case study for their implementation for solving problems in theoretical and practical cryptography. The ‘roadmap’ of the content of this also quite interesting.” (Panayiotis Vlamos, zbMATH 1480.00002, 2022)Table of ContentsMatrices and Matrix Algorithms.- Matrix Algebra.- Systems of Linear Equations.- Complex Numbers and Matrices.- Vector Spaces.- Vectors in a Three-Dimensional Space.- Equation of a Straight Line on a Plane.- Equation of a Plane in Space.- Equation of a Line in Space.- Bilinear and Quadratic Forms.- Curves of the Second-Order.- Elliptic Curves.- Appendix A, Basic Operators in Python and C.- Appendix B, Trigonometric Formulae.- Appendix C, The Greek Alphabet.- References.- Name Index.- Subject Index.
£54.99
Springer Nature Switzerland AG Probabilistic Graphical Models: Principles and
Book SynopsisThis fully updated new edition of a uniquely accessible textbook/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective. It features new material on partially observable Markov decision processes, causal graphical models, causal discovery and deep learning, as well as an even greater number of exercises; it also incorporates a software library for several graphical models in Python.The book covers the fundamentals for each of the main classes of PGMs, including representation, inference and learning principles, and reviews real-world applications for each type of model. These applications are drawn from a broad range of disciplines, highlighting the many uses of Bayesian classifiers, hidden Markov models, Bayesian networks, dynamic and temporal Bayesian networks, Markov random fields, influence diagrams, and Markov decision processes.Topics and features: Presents a unified framework encompassing all of the main classes of PGMs Explores the fundamental aspects of representation, inference and learning for each technique Examines new material on partially observable Markov decision processes, and graphical models Includes a new chapter introducing deep neural networks and their relation with probabilistic graphical models Covers multidimensional Bayesian classifiers, relational graphical models, and causal models Provides substantial chapter-ending exercises, suggestions for further reading, and ideas for research or programming projects Describes classifiers such as Gaussian Naive Bayes, Circular Chain Classifiers, and Hierarchical Classifiers with Bayesian Networks Outlines the practical application of the different techniques Suggests possible course outlines for instructors This classroom-tested work is suitable as a textbook for an advanced undergraduate or a graduate course in probabilistic graphical models for students of computer science, engineering, and physics. Professionals wishing to apply probabilistic graphical models in their own field, or interested in the basis of these techniques, will also find the book to be an invaluable reference.Dr. Luis Enrique Sucar is a Senior Research Scientist at the National Institute for Astrophysics, Optics and Electronics (INAOE), Puebla, Mexico. He received the National Science Prize en 2016.Table of ContentsPart I: FundamentalsIntroductionProbability TheoryGraph TheoryPart II: Probabilistic ModelsBayesian ClassifiersHidden Markov ModelsMarkov Random FieldsBayesian Networks: Representation and InferenceBayesian Networks: LearningDynamic and Temporal Bayesian NetworksPart III: Decision ModelsDecision GraphsMarkov Decision ProcessesPartially Observable Markov Decision Processes Part IV: Relational, Causal and Deep ModelsRelational Probabilistic Graphical ModelsGraphical Causal ModelsCausal DiscoveryDeep Learning and Graphical ModelsA: A Python Library for Inference and LearningGlossaryIndex
£54.99
Springer Nature Switzerland AG Algorithms and Complexity: 12th International Conference, CIAC 2021, Virtual Event, May 10–12, 2021, Proceedings
Book SynopsisThis book constitutes the refereed conference proceedings of the 12th International Conference on Algorithms and Complexity, CIAC 2019, held as a virtual event, in May 2021. The 28 full papers presented together with one invited lecture and 2 two abstracts of invited lectures were carefully reviewed and selected from 78 submissions. The International Conference on Algorithms and Complexity is intended to provide a forum for researchers working in all aspects of computational complexity and the use, design, analysis and experimentation of efficient algorithms and data structures. The papers present original research in the theory and applications of algorithms and computational complexity.Due to the Corona pandemic the conference was held virtually.Table of ContentsAbundant Extensions.- Three Problems on Well-Partitioned Chordal Graphs.- Distributed Distance-r Covering Problems on Sparse High-Girth Graphs.- Reconfiguration of Connected Graph Partitions via Recombination.- Algorithms for Energy Conservation in Heterogeneous Data Centers.- On Vertex-Weighted Graph Realizations.- On the Role of 3's for the 1-2-3 Conjecture.- Upper Tail Analysis of Bucket Sort and Random Tries.- Throughput Scheduling with Equal Additive Laxity.- Fragile Complexity of Adaptive Algorithms.- FPT and Kernelization Algorithms for the Induced Tree Problem.- A Tight Lower Bound for Edge-Disjoint Paths on Planar DAGs.- Upper Dominating Set: Tight Algorithms for Pathwidth and Sub-Exponential Approximation.- A Multistage View on 2-Satisfiability.- The Weisfeiler-Leman Algorithm and Recognition of Graph Properties.- The Parameterized Suffix Tray.- Exploring the Gap Between Treedepth and Vertex Cover Through Vertex Integrity.- Covering a Set of Line Segments with a Few Squares.- Circumventing Connectivity for Kernelization.- Online and Approximate Network Construction from Bounded Connectivity Constraints.- Globally Rigid Augmentation of Minimally Rigid Graphs in \(R^2\).- Extending Partial Representations of Rectangular Duals with Given Contact Orientations.- Can Local Optimality be Used for Efficient Data Reduction.- Colouring Graphs of Bounded Diameter in the Absence of Small Cycles.- Online Two-Dimensional Vector Packing with Advice.- Temporal Matching on Geometric Graph Data.
£64.99
Springer Nature Switzerland AG Guide to Discrete Mathematics: An Accessible Introduction to the History, Theory, Logic and Applications
This stimulating textbook presents a broad and accessible guide to the fundamentals of discrete mathematics, highlighting how the techniques may be applied to various exciting areas in computing. The text is designed to motivate and inspire the reader, encouraging further study in this important skill. Features: This book provides an introduction to the building blocks of discrete mathematics, including sets, relations and functions; describes the basics of number theory, the techniques of induction and recursion, and the applications of mathematical sequences, series, permutations, and combinations; presents the essentials of algebra; explains the fundamentals of automata theory, matrices, graph theory, cryptography, coding theory, language theory, and the concepts of computability and decidability; reviews the history of logic, discussing propositional and predicate logic, as well as advanced topics such as the nature of theorem proving; examines the field of software engineering, including software reliability and dependability and describes formal methods; investigates probability and statistics and presents an overview of operations research and financial mathematics.
£27.99
Springer Nature Switzerland AG Logic Functions and Equations: Fundamentals and
Book Synopsis The greatly expanded and updated 3rd edition of this textbook offers the reader a comprehensive introduction to the concepts of logic functions and equations and their applications across computer science and engineering. The authors’ approach emphasizes a thorough understanding of the fundamental principles as well as numerical and computer-based solution methods. The book provides insight into applications across propositional logic, binary arithmetic, coding, cryptography, complexity, logic design, and artificial intelligence.Updated throughout, some major additions for the 3rd edition include: a new chapter about the concepts contributing to the power of XBOOLE; a new chapter that introduces into the application of the XBOOLE-Monitor XBM 2; many tasks that support the readers in amplifying the learned content at the end of the chapters; solutions of a large subset of these tasks to confirm learning success; challenging tasks that need the power of the XBOOLE software for their solution. The XBOOLE-monitor XBM 2 software is used to solve the exercises; in this way the time-consuming and error-prone manipulation on the bit level is moved to an ordinary PC, more realistic tasks can be solved, and the challenges of thinking about algorithms leads to a higher level of education.Table of ContentsPart I Theoretical Foundations 1. Basic Algebraic Structures 2. Logic Functions 3. Logic Equations 4. Boolean Differential Calculus 5. Sets, Lattices, and Classes Logic Functions Part II Applications 6. Logics, Arithmetic, and Special Functions 7. SAT-Problems 8. Extremely Complex Problems 9. Combinational Circuits 10. Sequential Circuits References Index
£59.99