Algorithms and data structures Books
Oxford University Press Inc Algorithmic Puzzles
Book SynopsisAlgorithmic puzzles are puzzles involving well-defined procedures for solving problems. This book will provide an enjoyable and accessible introduction to algorithmic puzzles that will develop the reader''s algorithmic thinking.The first part of this book is a tutorial on algorithm design strategies and analysis techniques. Algorithm design strategies -- exhaustive search, backtracking, divide-and-conquer and a few others -- are general approaches to designing step-by-step instructions for solving problems. Analysis techniques are methods for investigating such procedures to answer questions about the ultimate result of the procedure or how many steps are executed before the procedure stops. The discussion is an elementary level, with puzzle examples, and requires neither programming nor mathematics beyond a secondary school level. Thus, the tutorial provides a gentle and entertaining introduction to main ideas in high-level algorithmic problem solving.The second and main part of the bTrade ReviewIndeed, I would say that this is a book that any mathematical puzzle enthusiast ought to consider buying. * Martin Griffiths, The Mathematical Gazette *Table of ContentsPreface ; List of Puzzles ; Tutorial Puzzles ; Main Section Puzzles ; 1. Tutorials ; General Strategies for Algorithm Design ; Analysis Techniques ; 2. Puzzles ; Easier Puzzles (#1 - #50) ; Medium Dic culty Puzzles (51 - 110) ; Harder Puzzles (#111 - 150) ; 3. Hints ; 4. Solutions ; References ; Design Strategy and Analysis Index ; Index of Terms and Names
£30.59
Pearson Education Data Structures and Algorithms
Book SynopsisThe authors' treatment of data structures in Data Structures and Algorithms is unified by an informal notion of "abstract data types," allowing readers to compare different implementations of the same concept. Algorithm design techniques are also stressed and basic algorithm analysis is covered. Most of the programs are written in Pascal.
£74.07
Manning Publications Quantum Programming in Depth
Book Synopsis
£56.32
Springer-Verlag New York Inc. Algorithms and Programming
Book SynopsisThis text is structured in a problem-solution format that requires the student to think through the programming process. New to the second edition are additional chapters on suffix trees, games and strategies, and Huffman coding as well as an Appendix illustrating the ease of conversion from Pascal to C.Trade ReviewFrom the reviews:"The book is addressed both to ambitious students and instructors looking for interesting problems [and] fulfills this task perfectly, especially if the reader has a good mathematical background." — Zentralblatt MATH"This book is intended for students, engineers, and other people who want to improve their computer skills.... The chapters can be read independently. Throughout the book, useful exercises give readers a feeling for how to apply the theory." — Computing Reviews"Overall...the book is well done. I recommend it to teachers and those wishing to sharpen their data structure and compiler skills." — SIGACT NewsFrom the reviews of the second edition:“An excellent source of material for college students … and for their teachers. … it contains a lot of great information for the computer science student. Ideally, students would acquire this book in their freshman year and begin using it as soon as they learn the basics of procedural programming. They will then find this book an excellent companion, as they develop their analytical and programming skills throughout the curriculum. … This book is a delight to read and work with. I highly recommend it.” (Edgar R. Chavez, ACM Computing Reviews, December, 2010)Table of ContentsVariables, expressions, assignments.- Generation of combinatorial objects.- Tree traversal (backtracking).- Sorting.- Finite-state algorithms in text processing.- Data types.- Recursion.- Recursive and non-recursive programs.- Graph algorithms.- Pattern matching.- Games analysis.- Optimal coding.- Set representation. Hashing.- Sets, trees, and balanced trees.- Context-free grammars.- Left-to-right parsing (LR).
£35.99
Centre for the Study of Language & Information Algorithmes
Book SynopsisThis book is a French translation of seventeen papers by Donald E. Knuth on algorithms both in the field of analysis of algorithms and in the design of new algorithms. They cover fundamental concepts and techniques and numerous discrete problems such as sorting, searching, data compression, theorem-proving, and cryptography, as well as methods for controlling errors in numerical computations.
£28.50
Elsevier Science Computability Complexity and Languages
Book SynopsisCovers the key areas of computer science, including recursive function theory, formal languages, and automata. This book is divided into five parts: Computability, Grammars and Automata, Logic, Complexity, and Unsolvability. It also covers in a variety of different arrangements automata theory, computational logic, and complexity theory.Trade Review"If there is a single book on the theory of computing that should be in every college library collection, this is it. Although written as a text for an advanced undergraduate course in theoretical computer science, the book may serve as an introductory resource, or the foundation for independent study, in many areas of theoretical computing: grammars, automata theory, computability, complexity theory, and unsolvability. The beauty of this book is that the breadth of coverage is complemented with extraordinary depth." --CHOICE "Theoretical computer science is often viewed as a collection of disparate topics, including computability theory, formal language theory, complexity theory, logic, and so on. This well-written book attempts to unify the subject by introducing each of these topics in turn, then showing how they relate to each other... This is an excellent book that succeeds in tying together a number of areas in theoretical computer science." --COMPUTING REVIEWSTable of ContentsPreliminaries. Computability: Programs and Computable Functions. Primitive Recursive Functions. A Universal Program. Calculations on Strings. Turing Machines. Processes and Grammars. Classifying Unsolvable Problems. Grammars and Automata: Regular Languages. Context-Free Languages. Context-Sensitive Languages. Logic: Propositional Calculus. Quantification Theory. Complexity: Abstract Complexity. PolynomialTime Computability. Semantics: Approximation Orderings. Denotational Semantics of Recursion Equations. Operational Semantics of Recursion Equations. Suggestions for Further Reading. Subject Index.
£47.49
Elsevier Science A Wavelet Tour of Signal Processing
Book SynopsisOffers the major concepts, techniques and applications of sparse representation. This book presents the standard representations with Fourier, wavelet and time-frequency transforms, and the construction of orthogonal bases with fast algorithms.Trade Review"There is no question that this revision should be published. Mallat’s book is the undisputed reference in this field – it is the only one that covers the essential material in such breadth and depth." --Laurent Demanet, Stanford UniversityTable of ContentsPrefaceNotationsSparse RepresentationsFourier KingdomDiscrete RevolutionTime Meets FrequencyFramesWavelet ZoomWavelet BasesWavelet Packet and Local Cosine BasesApproximations in BasesCompressionDenoisingSparse in Redundant DictionariesMathematical Complements
£72.00
Cambridge University Press Enterprise Liability and the Common Law
Book SynopsisProgramming languages should be designed not by piling feature on top of feature, but by removing the weaknesses and restrictions that make additional features appear necessary. Scheme demonstrates that a very small number of rules for forming expressions, with no restrictions on how they are composed, are enough to form a practical and efficient programming language that is flexible enough to support most of the major programming paradigms in use today. This book contains the three parts comprising 'R6RS', the sixth revision of a series of reports describing the programming language Scheme. The book is divided into parts: a description of the language itself, a description of the standard libraries and non-normative appendices. Early chapters introduce Scheme and later chapters act as a reference manual. This is an important report for programmers that work with or want to learn about the Scheme language.Table of ContentsPreface; Part I. Language: Description of the language; 1. Overview of Scheme; 2. Requirement levels; 3. Numbers; 4. Lexical syntax and datum syntax; 5. Semantic concepts; 6. Entry format; 7. Libraries; 8. Top-level programs; 9. Primitive syntax; 10. Expansion process; 11. Base library; Appendices; Part II. Standard Libraries: 12. Unicode; 13. Bytevectors; 14. List utilities; 15. Sorting; 16. Control structures; 17. Records; 18. Exceptions and conditions; 19. I/O; 20. File system; 21. Command-line access and exit values; 22. Arithmetic; 23. syntax-case; 24. Hashtables; 25. Enumerations; 26. Composite library; 27. Eval; 28. Mutable pairs; 29. Mutable strings; 30. R5RS compatibility; Part III. Non-Normative Appendices: A. Standard-conformant mode; B. Optional case insensitivity; C. Use of square brackets; D. Scripts; E. Source code representation; F. Use of library versions; G. Unique library names; References; Alphabetic index of definitions of concepts, keywords, and procedures.
£91.20
Cambridge University Press Data Structures and Algorithms Using Visual Basic.Net
Book SynopsisAt last, the VB.NET programmer has a dedicated reference - no more translating elementary material from C++ or Java. This is the only VB.NET book that provides comprehensive discussions of the major data structures and algorithms from the .NET Framework Class Library, as well as those that the programmer must develop.Trade ReviewChoosing which data structure and sorting algorithms to use can have a great effect on the speed of the program. This book helps programmers make those choices. This book begins with an introduction to properties and classes in VB.NET. It also describes the creation of a timing test in the VB.NET environment, which is used repeatedly in later chapters to demonstrate how different structures and searching techniques can change program completion time. This little bit of code is the prize inside, since it can be used whenever timing of VB.NET programming is needed…[This book] thoroughly covers the basics, and some more advanced topics of data structures and searching algorithms, using VB.NET with a minimalist approach. Computing ReviewsTable of Contents1. Collections; 2. Arrays and the array class; 3. The arraylist and sortedlist classes; 4. Basic sorting algorithms; 5. Basic searching algorithms; 6. Stacks and queues; 7. BitArrays and the BitVector structure; 8. Strings, the string class and the StringBuilder class; 9. Special string classes - StringCollection, StringDictionary and StringEnumerator; 10. Pattern matching and text processing - using the RegEx and supporting classes; 11. Hash tables; 12. Dictionaries - the DictionaryBase class and specialized dictionary classes; 13. Linked lists; 14. Binary trees and binary search trees; 15. Sets; 16. Advanced sorting algorithms; 17. Advanced searching algorithms; 18. Graphs and graph algorithms; 19. Greedy algorithms; 20. Probabilistic algorithms; 21. Dynamic programming.
£53.99
Cambridge University Press termrewritingandallthat
Book SynopsisThis textbook offers a unified and self-contained introduction to the field of term rewriting. It covers all the basic material (abstract reduction systems, termination, confluence, completion, and combination problems), but also some important and closely connected subjects: universal algebra, unification theory, GrÃbner bases and Buchberger's algorithm. The main algorithms are presented both informally and as programs in the functional language Standard ML (an appendix contains a quick and easy introduction to ML). Certain crucial algorithms like unification and congruence closure are covered in more depth and Pascal programs are developed. The book contains many examples and over 170 exercises. This text is also an ideal reference book for professional researchers: results that have been spread over many conference and journal articles are collected together in a unified notation, proofs of almost all theorems are provided, and each chapter closes with a guide to the literature.Trade Review'… a welcome and important addition to the library of any researcher interested in theoretical computer science. It provides a thorough grounding in the subject in a clear style, and gives plenty of indications of further directions, including an extensive bibliography'. The Computer Journal'… a well-balanced textbook … presenting the subject in a unified and systematic manner.' H. Herre, Zentralblatt MATH'… a highly welcome addition to the literature on term rewriting … It is very readable, well written and likeable book. it should be of great value to students and researchers alike.' Jan Willem Klop, Journal of Functioning ProgrammingTable of ContentsPreface; 1. Motivating examples; 2. Abstract reduction systems; 3. Universal algebra; 4. Equational problems; 5. Termination; 6. Confluence; 7. Completion; 8. Gröbner bases and Buchberger's algorithm; 9. Combination problems; 10. Equational unification; 11. Extensions; Appendix 1. Ordered sets; Appendix 2. A bluffer's guide to ML; Bibliography; Index.
£50.99
Cambridge University Press Algorithmic Game Theory
Book SynopsisMore than 40 of the top researchers in this field have written chapters that go from the foundations to the state of the art. Basic chapters on algorithmic methods for equilibria, mechanism design and combinatorial auctions are followed by chapters on incentives and pricing, cost sharing, information markets and cryptography and security.Trade Review'… a tome to be dipped into by researchers and developers who would want to know more about certain aspects of the field and particular 'state-of-the-art' issues and applications.' KybernetesTable of ContentsIntroduction Noam Nisan, Tim Roughgarden, Éva Tardos and Vijay V. Vazirani; Part I. Computing in Games: 1. Basic solution concepts and computational issues Éva Tardos and Vijay V. Vazirani; 2. Algorithms for equilibria Christos Papadimitriou; 3. Equilibrium computation for games in strategic and extensive form Bernhard von Stengel; 4. Learning, regret minimization and correlated equilibria Avrim Blum and Yishay Mansour; 5. Graphical games Michael J. Kearns; 6. Cryptography and game theory Yevgeniy Dodis and Tal Rabin; 7. Combinatorial algorithms for market equilibria Vijay V. Vazirani; 8. Computation of market equilibria by convex programming Bruno Codenotti and Kasturi Varadarajan; Part II. Algorithmic Mechanism Design: 9. Introduction to mechanism design (for computer scientists) Noam Nisan; 10. Mechanism design without money James Schummer and Rakesh V. Vohra; 11. Combinatorial auctions Noam Nisan and Liad Blumrosen; 12. Computationally efficient approximation mechanisms Ron Lavi; 13. Profit maximization in mechanism design Jason Hartline and Anna Karlin; 14. Distributed algorithmic mechanism design Joan Feigenbaum, Michael Schapira and Scott Shenker; 15. Cost sharing Kamal Jain and Mohammad Mahdian; 16. On-line mechanisms David C. Parkes; Part III. Quantifying the Inefficiency of Equilibria: 17. Introduction to the inefficiency of equilibria Tim Roughgarden and Éva Tardos; 18. Routing games Tim Roughgarden; 19. Inefficiency of equilibria in network formation games Éva Tardos and Tom Wexler; 20. Selfish load-balancing Berthold Vöcking; 21. Efficiency loss and the design of scalable resource allocation mechanisms Ramesh Johari; Part IV. Additional Topics: 22. Incentives and pricing in communication networks Asuman Ozdaglar and R. Srikant; 23. Incentives in peer-to-peer systems John Chuang, Michal Feldman and Moshe Babaioff; 24. Cascading behavior in networks: algorithmic and economic issues Jon Kleinberg; 25. Incentives and information security Ross Anderson, Tyler Moore, Shishir Nagaraja and Andy Ozment; 26. Computational aspects of information markets David M. Pennock and Rahul Sami; 27. Manipulation-resistant reputation systems Eric Friedman, Paul Resnick and Rahul Sami; 28. Sponsored search auctions Sebastien Lahaie, David M. Pennock, Amin Saberi and Rakesh V. Vohra; 29. Algorithmic issues in evolutionary game theory Michael Kearns and Siddharth Suri.
£59.99
Cambridge University Press Advanced Data Structures
Book SynopsisThis graduate-level text explains the implementation and analysis of data structures as a specialised topic in applied algorithms. It examines efficient ways to realise query operations and the history of various structures as they are related to basic concepts of data storage.Trade Review'I think this book is well suited as a main or supplemental text in a graduate-level data structures course, not to mention an invaluable desk reference for those interested in implementing the advance structures outlined in this book. This book was a joy to review, and deserves a place on my bookshelf.' SIGACT News'It can be briefly said that the reader will be dealing with an illustration, diagram, and code packed book, that will do it's best not to confuse but to very well explain one of the toughest computer science subjects, and he will be pleasantly surprised to learn many new-age data structures.' Igor Gvero, Software Engineering NotesTable of Contents1. Elementary structures; 2. Search types; 3. Balanced search trees; 4. Tree structures for sets of intervals; 5. Heaps; 6. Union-find and related structures; 7. Data structure transformations; 8. Data structures for strings; 9. Hash tables; 10. Appendix.
£77.00
£26.77
Cambridge University Press Mathematics of Public Key Cryptography
Book SynopsisPublic key cryptography is a major interdisciplinary subject with many real-world applications. This book has been carefully written to communicate the major ideas and techniques in this subject to a wide readership. With numerous examples and exercises, it is suitable as a textbook for an advanced course or for self-study.Trade Review'… the book gathers the main mathematical topics related to public key cryptography and provides an excellent source of information for both students and researchers interested in the field.' Juan Tena Ayuso, Zentralblatt MATHTable of ContentsPreface; Acknowledgements; 1. Introduction; Part I. Background: 2. Basic algorithmic number theory; 3. Hash functions and MACs; Part II. Algebraic Groups: 4. Preliminary remarks on algebraic groups; 5. Varieties; 6. Tori, LUC and XTR; 7. Curves and divisor class groups; 8. Rational maps on curves and divisors; 9. Elliptic curves; 10. Hyperelliptic curves; Part III. Exponentiation, Factoring and Discrete Logarithms: 11. Basic algorithms for algebraic groups; 12. Primality testing and integer factorisation using algebraic groups; 13. Basic discrete logarithm algorithms; 14. Factoring and discrete logarithms using pseudorandom walks; 15. Factoring and discrete logarithms in subexponential time; Part IV. Lattices: 16. Lattices; 17. Lattice basis reduction; 18. Algorithms for the closest and shortest vector problems; 19. Coppersmith's method and related applications; Part V. Cryptography Related to Discrete Logarithms: 20. The Diffie–Hellman problem and cryptographic applications; 21. The Diffie–Hellman problem; 22. Digital signatures based on discrete logarithms; 23. Public key encryption based on discrete logarithms; Part VI. Cryptography Related to Integer Factorisation: 24. The RSA and Rabin cryptosystems; Part VII. Advanced Topics in Elliptic and Hyperelliptic Curves: 25. Isogenies of elliptic curves; 26. Pairings on elliptic curves; Appendix A. Background mathematics; References; Author index; Subject index.
£56.99
Cambridge University Press Fundamentals of Stream Processing Application Design Systems and Analytics
Book SynopsisStream processing is a novel distributed computing paradigm that supports the gathering, processing and analysis of high-volume, heterogeneous, continuous data streams, to extract insights and actionable results in real time. This comprehensive, hands-on guide combining the fundamental building blocks and emerging research in stream processing is ideal for application designers, system builders, analytic developers, as well as students and researchers in the field. This book introduces the key components of the stream computing paradigm, including the distributed system infrastructure, the programming model, design patterns and streaming analytics. The explanation of the underlying theoretical principles, illustrative examples and implementations using the IBM InfoSphere Streams SPL language and real-world case studies provide students and practitioners with a comprehensive understanding of such applications and the middleware that supports them.Table of ContentsPart I. Fundamentals: 1. What brought us here?; 2. Introduction to stream processing; Part II. Application Development: 3. Application development - the basics; 4. Application development - data flow programming; 5. Large-scale development - modularity, extensibility, and distribution; 6. Application engineering - debugging and visualization; Part III. System Architecture: 7. Architecture of a stream processing system; 8. InfoSphere streams architecture; Part IV. Application Design and Analytics: 9. Design principles and patterns for stream processing applications; 10. Stream processing and mining algorithms; Part V. Case Studies: 11. End-to-end application examples; Part VI. Closing Notes: 12. Conclusion.
£79.79
Cambridge University Press Calendrical Calculations
Book SynopsisThis unique resource now includes coverage of Unix dates, Italian time, the Akan, Icelandic, Saudi Arabian Umm al-Qura, Babylonian, Samaritan, and Nepalese calendars, plus expanded treatments of Islamic and Hebrew calendars. The astronomical functions have been rewritten for more accurate results and include calculations of moonrise and moonset.Trade Review'It retains all the features that made the first edition … such a wonderful resource, while adding much new material … If you are at all interested in time and calendars, this book must find a place on your desk.' Victor J. Katz, Mathematical ReviewsTable of Contents1. Calendar basics; Part I. Arithmetical Calendars: 2. The Gregorian calendar; 3. The Julian calendar; 4. The Coptic and Ethiopic calendars; 5. The ISO calendar; 6. The Icelandic calendar; 7. The Islamic calendar; 8. The Hebrew calendar; 9. The Ecclesiastical calendars; 10. The old Hindu calendars; 11. The Mayan calendars; 12. The Balinese Pawukon calendar; 13. Generic Cyclical calendars; Part II. Astronomical Calendars: 14. Time and astronomy; 15. The Persian calendar; 16. The Bahá'í calendar; 17. The French Revolutionary calendar; 18. Astronomical Lunar calendars; 19. The Chinese calendar; 20. The modern Hindu calendars; 21. The Tibetan calendar; Part III. Appendices: A. Function, parameter, and constant types; B. Cross references; C. Sample data; D. Lisp implementation.
£97.85
Cambridge University Press Concentration of Measure for the Analysis of Randomized Algorithms
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.
£36.89
Apress Pro Data Backup and Recovery Experts Voice in Data Management
Table of Contents Introduction to Backup and Recovery Backup Software Physical Backup Media Virtual Backup Media New Media Technologies Software Architectures: CommVault Software Architectures: NetBackup Application Backup Strategies Putting It All Together: Sample Backup Environments Monitoring and Reporting Summary
£47.49
Apress Beginning Oracle SQL
Book SynopsisBeginning Oracle SQL is your introduction to the interactive query tools and specific dialect of SQL used with Oracle Database.Table of Contents1. Relational Database Systems and Oracle2. Introduction to SQL and SQL*Plus, and SQL Developer3. Data Definition, Part I4. Retrieval: The Basics5. Retrieval: Functions6. Data Manipulation7. Data Definition, Part II8. Retrieval: Joins and Grouping9. Retrieval: Advanced Features10. Views11. Automating12. Object-Relational Features13. Appendix A – Case Tables14. Appendix B – Exercise Solutions
£58.49
Taylor & Francis Inc Fundamentals of Dependable Computing for Software Engineers
Book SynopsisFundamentals of Dependable Computing for Software Engineers presents the essential elements of computer system dependability. The book describes a comprehensive dependability-engineering process and explains the roles of software and software engineers in computer system dependability. Readers will learn: Why dependability matters What it means for a system to be dependable How to build a dependable software system How to assess whether a software system is adequately dependable The author focuses on the actions needed to reduce the rate of failure to an acceptable level, covering material essential for engineers developing systems with extreme consequences of failure, such as safety-critical systems, security-critical systems, and critical infrastructure systems. The text explores the systems engineering aspects of dependability and provides a framework for engineers to reason and make deTrade ReviewThe book is an important addition to one’s bookshelf. … it is insightful, close to faultless, and a wonderful reference. Read it from front to back and cite it in your proposals and professional and scholarly papers. … This book can and should be taught as part of an undergraduate or graduate software engineering program. I wish it had been available when I was setting up a graduate software engineering program … .—Larry Bernstein, Computing Reviews, June 2012This book takes full advantage of the extensive work that has been undertaken over many years on the creation of a rich set of system dependability concepts. John Knight makes excellent use of these concepts in producing a very well-argued and comprehensive account, aimed squarely at software engineers, of the variety of dependability issues they are likely to find in real systems and of the strategies that they should use to address these issues. Appropriately qualified students who study this book thoroughly and computer professionals seeking a greater understanding of the various dependability-related problems that they have encountered already in their careers should gain much from this book. I therefore take great pleasure in enthusiastically recommending it to both classes of reader.—From the Foreword by Brian Randell, Newcastle University, UKTable of ContentsIntroduction. Dependability Requirements. Errors, Faults, and Hazards. Dependability Analysis. Dealing with Faults. Degradation Faults and Software. Software Dependability. Software Fault Avoidance in Specification. Software Fault Avoidance in Implementation. Software Fault Elimination. Software Fault Tolerance. Dependability Assessment. Bibliography.
£46.79
£26.77
Springer Us RealTime Systems Engineering and Applications Engineering And Applications 167 The Springer International Series in Engineering and Computer Science
Book SynopsisThe Origins of Real-Time Processing.- The Concept of Time in the Specification of Real-Time Systems.- Language-Independent Schedulability Analysis of Real-Time Programs.- Which Theory Matches Automation Engineering?.- Requirements Engineering for Real-Time and Embedded Systems.- Real-Time Programming Languages.- Comparison of Synchronization Concepts.- Real-Time Database Systems.- Microprocessor Architectures: A Basis for Real-Time Systems.- Buses in Real-Time Environments.- Distributed Systems for Real Time Applications.- Robot Programming.- Real-Time Data Processing of the Sensory Data of a Multi- Fingered Dextrous Robot Hand.- Fly-By-Wire Systems for Military High Performance Aircraft.- Artificial Intelligence Techniques in Real-Time Processing.- Recommendations for a Real-Time Systems Curriculum.Table of ContentsForeword. I: Introduction. 1. The Origins of Real-Time Processing; M. Schiebe. II: Theoretical Foundations. 2. The Concept of Time in the Specification of Real-Time Systems; B. Hoogeboom, W.A. Halang. 3. Language-Independent Schedulability Analysis of Real-Time Programs; A.D. Stoyenko. III: Models and Tools 4. Which Theory Matches Automation Engineering? Petri-Nets as a Formal Basis; E. Schnieder. 5. Requirements Engineering for Real-Time and Embedded Systems; P. Hruschka. IV: Practical Considerations. 6. Real-Time Programming Languages; W.A. Halang, K.-O. Mangold. 7. Comparison of Synchronization Concepts of Ada, Concurrent C and PEARL; K.-F. Gebhardt. 8. Real-Time Database Systems; H. Windauer. 9. Microprocessor Architectures: A Basis for Real-Time Systems; T. Bemmerl. 10. Buses in Real-Time Environments; F. Demmelmeier. 11. Distributed Systems for Real-Time Applications Using Manufacturing Automation as an Example; H. Rzehak. 12. Robot Programming; K. Fischer, B. Glavina, E. Hagg, G. Schrott, J. Schweiger, H.-J. Siegert. V: Examples for Applications. 13. Real-Time Data Processing of the Sensory Data of Multi-Fingered Dextrous Hand; A. Knoll. 14. Fly-By-Wire Systems for Military High Performance Aircraft; D. Langer, J. Rauch, M. Rößler. VI: Future Developments. 15. Artificial Intelligence Techniques in Real-Time Processing; K. Kratzer. 16. Recommendations for a Real-Time Systems Curriculum; W.A. Halang. Glossary. Index.
£189.99
Springer New York Number Theory
Book SynopsisThis book deals with several aspects of what is now called "explicit number theory." The local aspect, global aspect, and the third aspect is the theory of zeta and L-functions.Trade ReviewFrom the reviews:"Cohen (Université Bordeaux I, France), an instant classic, uniquely bridges the gap between old-fashioned, naive treatments and the many modern books available that develop the tools just mentioned … . Summing Up: Recommended. … Upper-division undergraduates through faculty." (D. V. Feldman, CHOICE, Vol. 45 (5), January, 2008)"The book deals with aspects of ‘explicit number theory’. … The central theme … is the solution of Diophantine equations. … It combines an interesting ‘philosophy’ of the subject with an encyclopedic grasp of detail. The extension of the author’s reach via the contributed chapters is a good idea. Perhaps it is the start of a trend, as the subject grows more and more. … It will undoubtedly be mined by instructors for their graduate courses, particularly for the purpose of including some recently-proved content." (R. C. Baker, Mathematical Reviews, Issue 2008 e)“This is the second volume of a highly impressive two-volume textbook on Diophantine analysis. … readers are presented with an almost overwhelming amount of material. This … text book is bound to become an important reference for students and researchers alike.” (C. Baxa, Monatshefte für Mathematik, Vol. 157 (2), June, 2009)Table of ContentsAnalytic Tools.- Bernoulli Polynomials and the Gamma Function.- Dirichlet Series and L-Functions.- p-adic Gamma and L-Functions.- Modern Tools.- Applications of Linear Forms in Logarithms.- Rational Points on Higher-Genus Curves.- The Super-Fermat Equation.- The Modular Approach to Diophantine Equations.- Catalan’s Equation.
£42.74
Springer New York Modern Graph Theory
Book SynopsisPresents an account of graph theory. Written with students of mathematics and computer science in mind, this book reflects the state of the subject and emphasizes connections with other branches of pure mathematics. It presents a survey of fresh topics and includes more than 600 exercises.Trade Review"...This book is likely to become a classic, and it deserves to be on the shelf of everyone working in graph theory or even remotely related areas, from graduate student to active researcher."--MATHEMATICAL REVIEWSTable of Contents1: Fundamentals. 2: Electrical Networks. 3: Flows, Connectivity and Matching. 4: Extremal Problems. 5: Colouring. 6: Ramsey Theory. 7: Random Graphs. 8: Graphs, Groups and Matrices. 9: Random Walks on Graphs. 10: The Tutte Polynomial.
£41.79
Springer London Game of Life Cellular Automata
Book SynopsisIn the late 1960s British mathematician John Conway invented a virtual mathematical machine that operates on a two-dimensional array of square cell. A dead cell comes to life if it has exactly three live neighbours. A live cell remains alive if two or three of its neighbours are alive, otherwise the cell dies.Trade ReviewFrom the reviews:“This volume’s 27 papers offer some systematic methods and rigorous theorems that exhibit the study of Conway’s game and its variations, emerging out of the realm of merely recreational mathematics. … this unique book will have great value as both a state-of-the-art summary and a collection of proposals for new directions to explore. Summing Up: Highly recommended. Upper-division undergraduates through professionals.” (D. V. Feldman, Choice, Vol. 48 (4), December, 2010)“Andrew Adamatzky has assembled a superb collection of papers on Life that encompass work going back more than 20 years. … maintains a good balance between interconnectedness and recognition of the papers as independent contributions. … This book is a treasure trove of history, concepts, and models. It is a good starting place for a newcomer to the study of Conway’s Game of Life, an opening of vistas for the amateur hobbyist, and a serious handbook for the professional researcher.” (Anthony J. Duben, ACM Computing Reviews, February, 2011)Table of Contents1. Introduction to Cellular Automata and Conway’s Game of Life.- Part I Historical.- 2. Conway’s Game of Life: Early Personal Recollections.- 3. Conway’s Life.- 4. Life’s Still Lifes.- 5. A Zoo of Life Forms.- Part II Classical Topics.- 6. Growth and Decay in Life-Like Cellular Automata.- 7. The B36/S125 “2x2” Life-Like Cellular Automaton.- 8. Object Synthesis in Conway’s Game of Life and other Cellular Automata.- 9. Gliders and Glider Guns Discovery in Cellular Automata.- 10. Constraint Programming to Solve Maximal Density Still Life.- Part III Asynchronous, Continuous and Memory-Enriched Automata.- 11. Larger than Life’s Extremes: Rigorous Results for Simplified Rules and Speculation on the Phase Boundaries.- 12. RealLife.- 13. Variations on the Game of Life.- 14. Does Life Resist Asynchrony?.- 15. LIFE with Short-Term Memory.- 16. Localization Dynamics in a Binary Two-Dimensional Cellular Automaton: the Diffusion Rule.- Part IV Non-Orthogonal Lattices.- 17. The Game of Life in Non-Square Environments.- 18. The Game of Life Rules on Penrose Tilings: Still Life and Oscillators.- 19. A Spherical XOR Gate Implemented in the Game of Life.- Part V Complexity.- 20. Emergent Complexity in Conway’s Game of Life.- 21. Macroscopic Spatial Complexity of the Game of Life Cellular Automaton: A Simple Data Analysis.- Part VI Physics.- 22. The Enlightened Game of Life 23. Towards a Quantum Game of Life.- Part VII Music.- 24. Game of Life Music.- Part VIII Computation.- 25. Universal Computation and Construction in GoL Cellular Automata.- 26. A Simple Universal Turing Machine for the Game of Life Turing Machine.- 27. Computation with Competing Patterns in Life-like Automaton.- Index
£116.99
ISTE Ltd and John Wiley & Sons Inc A Textbook of Data Structures and Algorithms,
Book SynopsisData structures and algorithms is a fundamental course in Computer Science, which enables learners across any discipline to develop the much-needed foundation of efficient programming, leading to better problem solving in their respective disciplines. A Textbook of Data Structures and Algorithms is a textbook that can be used as course material in classrooms, or as self-learning material. The book targets novice learners aspiring to acquire advanced knowledge of the topic. Therefore, the content of the book has been pragmatically structured across three volumes and kept comprehensive enough to help them in their progression from novice to expert. With this in mind, the book details concepts, techniques and applications pertaining to data structures and algorithms, independent of any programming language. It includes 181 illustrative problems and 276 review questions to reinforce a theoretical understanding and presents a suggestive list of 108 programming assignments to aid in the implementation of the methods covered.Table of ContentsPreface xi Acknowledgments xvii Chapter 13 Hash Tables 1 13.1 Introduction 1 13.1.1 Dictionaries 1 13.2 Hash table structure 2 13.3 Hash functions 4 13.3.1 Building hash functions 4 13.4 Linear open addressing 5 13.4.1 Operations on linear open addressed hash tables 8 13.4.2 Performance analysis 10 13.4.3 Other collision resolution techniques with open addressing 11 13.5 Chaining 13 13.5.1 Operations on chained hash tables 15 13.5.2 Performance analysis 17 13.6 Applications 18 13.6.1 Representation of a keyword table in a compiler 18 13.6.2 Hash tables in the evaluation of a join operation on relational databases 19 13.6.3 Hash tables in a direct file organization 22 13.7 Illustrative problems 23 Chapter 14 File Organizations 33 14.1 Introduction 33 14.2 Files 34 14.3 Keys 36 14.4 Basic file operations 38 14.5 Heap or pile organization 38 14.5.1 Insert, delete and update operations 39 14.6 Sequential file organization 39 14.6.1 Insert, delete and update operations 39 14.6.2 Making use of overflow blocks 40 14.7 Indexed sequential file organization 41 14.7.1 Structure of the ISAM files 41 14.7.2 Insert, delete and update operations for a naïve ISAM file 42 14.7.3 Types of indexing 43 14.8 Direct file organization 48 14.9 Illustrative problems 50 Chapter 15 k-d Trees and Treaps 61 15.1 Introduction 61 15.2 k-d trees: structure and operations 61 15.2.1 Construction of a k-d tree 65 15.2.2 Insert operation on k-d trees 69 15.2.3 Find minimum operation on k-d trees 70 15.2.4 Delete operation on k-d trees 72 15.2.5 Complexity analysis and applications of k-d trees 74 15.3 Treaps: structure and operations 76 15.3.1 Treap structure 76 15.3.2 Operations on treaps 77 15.3.3 Complexity analysis and applications of treaps 82 15.4 Illustrative problems 83 Chapter 16 Searching 93 16.1 Introduction 93 16.2 Linear search 94 16.2.1 Ordered linear search 94 16.2.2 Unordered linear search 94 16.3 Transpose sequential search 96 16.4 Interpolation search 98 16.5 Binary search 100 16.5.1 Decision tree for binary search 101 16.6 Fibonacci search 104 16.6.1 Decision tree for Fibonacci search 105 16.7 Skip list search 108 16.7.1 Implementing skip lists 112 16.7.2 Insert operation in a skip list 113 16.7.3 Delete operation in a skip list 114 16.8 Other search techniques 116 16.8.1 Tree search 116 16.8.2 Graph search 116 16.8.3 Indexed sequential search 116 16.9 Illustrative problems 118 Chapter 17 Internal Sorting 131 17.1 Introduction 131 17.2 Bubble sort 132 17.2.1 Stability and performance analysis 134 17.3 Insertion sort 135 17.3.1 Stability and performance analysis 136 17.4 Selection sort 138 17.4.1 Stability and performance analysis 140 17.5 Merge sort 140 17.5.1 Two-way merging 141 17.5.2 k-way merging 143 17.5.3 Non-recursive merge sort procedure 144 17.5.4 Recursive merge sort procedure 145 17.6 Shell sort 147 17.6.1 Analysis of shell sort 153 17.7 Quick sort 153 17.7.1 Partitioning 153 17.7.2 Quick sort procedure 156 17.7.3 Stability and performance analysis 158 17.8 Heap sort 159 17.8.1 Heap 159 17.8.2 Construction of heap 160 17.8.3 Heap sort procedure 163 17.8.4 Stability and performance analysis 167 17.9 Radix sort 167 17.9.1 Radix sort method 167 17.9.2 Most significant digit first sort 171 17.9.3 Performance analysis 171 17.10 Counting sort 171 17.10.1 Performance analysis 175 17.11 Bucket sort 175 17.11.1 Performance analysis 178 17.12 Illustrative problems 179 Chapter 18 External Sorting 197 18.1 Introduction 197 18.1.1 The principle behind external sorting 197 18.2 External storage devices 198 18.2.1 Magnetic tapes 199 18.2.2 Magnetic disks 200 18.3 Sorting with tapes: balanced merge 202 18.3.1 Buffer handling 204 18.3.2 Balanced P-way merging on tapes 205 18.4 Sorting with disks: balanced merge 206 18.4.1 Balanced k-way merging on disks 207 18.4.2 Selection tree 208 18.5 Polyphase merge sort 212 18.6 Cascade merge sort 214 18.7 Illustrative problems 216 Chapter 19 Divide and Conquer 229 19.1 Introduction 229 19.2 Principle and abstraction 229 19.3 Finding maximum and minimum 231 19.3.1 Time complexity analysis 232 19.4 Merge sort 233 19.4.1 Time complexity analysis 233 19.5 Matrix multiplication 234 19.5.1 Divide and Conquer-based approach to “high school” method of matrix multiplication 234 19.5.2 Strassen’s matrix multiplication algorithm 236 19.6 Illustrative problems 239 Chapter 20 Greedy Method 245 20.1 Introduction 245 20.2 Abstraction 245 20.3 Knapsack problem 246 20.3.1 Greedy solution to the knapsack problem 247 20.4 Minimum cost spanning tree algorithms 249 20.4.1 Prim’s algorithm as a greedy method 250 20.4.2 Kruskal’s algorithm as a greedy method 250 20.5 Dijkstra’s algorithm 251 20.6 Illustrative problems 251 Chapter 21 Dynamic Programming 261 21.1 Introduction 261 21.2 0/1 knapsack problem 263 21.2.1 Dynamic programming-based solution 264 21.3 Traveling salesperson problem 266 21.3.1 Dynamic programming-based solution 267 21.3.2 Time complexity analysis and applications of traveling salesperson problem 269 21.4 All-pairs shortest path problem 269 21.4.1 Dynamic programming-based solution 270 21.4.2 Time complexity analysis 272 21.5 Optimal binary search trees 272 21.5.1 Dynamic programming-based solution 274 21.5.2 Construction of the optimal binary search tree 276 21.5.3 Time complexity analysis 279 21.6 Illustrative problems 280 Chapter 22 P and NP Class of Problems 287 22.1 Introduction 287 22.2 Deterministic and nondeterministic algorithms 289 22.3 Satisfiability problem 292 22.3.1 Conjunctive normal form and Disjunctive normal form 294 22.3.2 Definition of the satisfiability problem 294 22.3.3 Construction of CNF and DNF from a logical formula 295 22.3.4 Transformation of a CNF into a 3-CNF 296 22.3.5 Deterministic algorithm for the satisfiability problem 297 22.3.6 Nondeterministic algorithm for the satisfiability problem 297 22.4 NP-complete and NP-hard problems 297 22.4.1 Definitions 298 22.5 Examples of NP-hard and NP-complete problems 300 22.6 Cook’s theorem 302 22.7 The unsolved problem P = NP 303 22.8 Illustrative problems 304 References 311 Index 313 Summaries of other volumes 317
£112.50
Royal Society of Chemistry Knowledge-based Expert Systems in Chemistry:
Book SynopsisThere have been significant developments in the use of knowledge-based expert systems in chemistry since the first edition of this book was published in 2009. This new edition has been thoroughly revised and updated to reflect the advances. The underlying theme of the book is still the need for computer systems that work with uncertain or qualitative data to support decision-making based on reasoned judgements. With the continuing evolution of regulations for the assessment of chemical hazards, and changes in thinking about how scientific decisions should be made, that need is ever greater. Knowledge-based expert systems are well established in chemistry, especially in relation to toxicology, and they are used routinely to support regulatory submissions. The effectiveness and continued acceptance of computer prediction depends on our ability to assess the trustworthiness of predictions and the validity of the models on which they are based. Written by a pioneer in the field, this book provides an essential reference for anyone interested in the uses of artificial intelligence for decision making in chemistry.Table of ContentsArtificial Intelligence – Making Use of Reasoning; Synthesis Planning by Computer;Other Programs to Support Chemical Synthesis Planning; International Repercussions of the Harvard LHASA Project; Current Interest in Synthesis Planning by Computer; Structure Representation; Structure, Substructure and Superstructure Searching; Protons That Come and Go; Aromaticity and Stereochemistry; DEREK – Predicting Toxicity; Other Alert-based Toxicity Prediction Systems; Rule Discovery; The 2D–3D Debate; Making Use of Reasoning: Derek for Windows; Predicting Metabolism; Relative Reasoning; Predicting Biodegradation; Other Applications and Potential Applications of Knowledge-based Prediction in Chemistry; Combining Predictions; The Adverse Outcome Pathways Approach; Evaluation of Knowledge-based Systems; Validation of Computer Predictions; Artificial Intelligence Developments in Other Fields; A Subjective View of the Future
£141.55
Bonnier Books Ltd Filterworld: How Algorithms Flattened Culture
Book Synopsis'The story told here is instrumental to your own' - Jared Lanier 'Timely, erudite, important' - Ayad Akhtar What happens when our cultural and artistic lives are dictated to us by an algorithm? What does it mean when shareability supersedes innovation? How can we make a choice when the options have been so carefully arranged for us? From coffee shops to city grids to TikTok feeds and Netflix homepages the world over, algorithmic recommendations prescribe our experiences. This network of mathematically determined choices - the 'Filterworld' - has taken over, almost unnoticed, as we've grown accustomed to an insipid new normal. But to have our tastes, behaviours, and emotions governed by computers calls the very notion of free will into question. Internationally recognized journalist and New Yorker staff writer Kyle Chayka journeys through this ever-tightening web woven by algorithms. He explores how online and offline spaces alike have been engineered for seamless consumption. How the lowest common denominator is promoted at the expense of the complex, diverse or challenging. How users of technology contend with data-driven equations that promise to anticipate their desires but often get them wrong. How the FIlterworld is determining the very shape of culture itself. Chayka skilfully and compellingly traces this creeping, machine-guided curation that influences not just what culture we consume, but what culture is produced. In doing so, he attempts to answer to the most urgent question currently facing us: is personal freedom ever again possible on the Internet?Filterworld is a fascinating history of the rise of the algorithm and an important investigation into where it could take us next - if we let it.Trade Review'Necessary reading for anyone who has wondered just how, in expanding our world, the internet has ended up emptying our experience of it. [...] Timely, erudite, important.' -- Ayad Akhtar, Pulitzer Prize winner and author of Homeland Elegies'Kyle Chayka is a vital observer of how digital technology shapes our culture, and Filterworld will change how you think about the internet. In his invigorating new book, Chayka demonstrates how everything from movies to music, design, media, and travel is at the mercy of algorithms.' -- Ben Smith, author of Traffic: Genius, Rivalry, and Delusion in the Billion-Dollar Race to Go Viral'Filterworld is a vital interrogation of algorithmic technology and its unrelenting power in shaping both our online and offline experiences. Chayka deftly explains how today's social media ecosystem operates and, more importantly, reveals a way out of the ever-tightening grip of this stifling digital filtration. [...] Filterworld is required reading for anyone who uses the Internet.' -- Taylor Lorenz, author of Extremely Online...'Filterworld skillfully interrogates how the giant project of measuring humanity using the internet turned into an unfortunate modification of humanity. The story told here is instrumental to your own, even if you do not realize it.' -- Jaron Lanier, author of Dawn of the New Everything and The Father of Virtual Reality'An essential book for anyone questioning if their phones are "listening" to them.' * i-D *'The promise of the Internet is that it is boundless, full of original content and unique cultural connections. So why does everything look, sound and feel the same? Kyle Chayka's insightful and timely book explains how big tech's algorithms have homogenized our experiences for profit, and too often left us poorer for it.' -- James Griffiths, author of The Great Firewall of China and Speak Not'Filterworld incisively diagnoses a problem that I've long felt but struggled to name and is the most convincing explanation I've encountered for why so many of our cultural products carry an uncanny whiff of familiarity. Amidst cheers for the death of the monoculture, Chayka offers a sharp and necessary counterpoint, demonstrating how mass culture, even as it diffuses into niche datastreams, trends toward a vacuous mean.' -- Meghan O’Gieblyn, author of God, Human, Animal, Machine
£20.90
Packt Publishing Limited Unreal Engine 4 Game Development Quick Start
Book SynopsisLearn how to use Unreal Engine 4 by building 3D and multiplayer games using BlueprintsKey Features Learn the fundamentals of Unreal Engine such as project templates, Blueprints, and C++ Learn to design games; use UMG to create menus and HUDs, and replication to create multiplayer games Build dynamic game elements using Animation Blueprints and Behavior Trees Book DescriptionUnreal Engine is a popular game engine for developers to build high-end 2D and 3D games.This book is a practical guide, starting off by quickly introducing you to the Unreal Engine 4 (UE4) ecosystem. You will learn how to create Blueprints and C++ code to define your game's functionality. You will be familiarized with the core systems of UE4 such as UMG, Animation Blueprints, and Behavior Trees. You will also learn how to use replication to create multiplayer games. By the end of this book, you will have a broad, solid knowledge base to expand upon on your journey with UE4.What you will learn Use project templates to give your game a head start Create custom Blueprints and C++ classes and extend from Epic's base classes Use UMG to create menus and HUDs for your game Create more dynamic characters using Animation Blueprints Learn how to create complex AI with Behavior Trees Use replication to create multiplayer games Optimize, test, and deploy a UE4 project Who this book is forReaders who already have some game development experience and Unity users who would like to try UE4 will all benefit from this book. Knowledge of basic Object-Oriented Programming topics such as variables, functions, and classes is assumed.Table of ContentsTable of Contents Introduction to Unreal Engine 4 Programming Using Blueprints Adding C++ to a Blueprint Project Creating HUDs and Menus Using UMG Animation Blueprints AI with Behavior Tree and Blackboard Multiplayer Games Optimization, Testing, and Packaging
£999.99
Pino Luca Mastering Python: How to learn Python Easily and
Book Synopsis
£24.55
Emerald Publishing Limited Organization and Governance Using Algorithms
Book SynopsisFollowing a recent mathematical, algorithmic, and computational turn in the field of social sciences, and particularly design aspects of contemporary organisations, Organisation and Governance Using Algorithms explores the problem of governance in organisations from a mathematical perspective. Avramopoulos offers a ground-breaking theory and application on organisational systems design, including discussions on organisational systems design requirements, such as productivity, emotion, and reward, the problems of unaccountability, including hierarchical delegation, and the benefits of accountable design. The suggested theoretical approach views organizational actors as computer processors that communicate through a shared infrastructure – both physical and digital – and suggests scientific principles and mechanisms by which to correct inequality and advance democratic governance in organisations.Table of ContentsChapter 1. Introduction Chapter 2. On the cognitive foundation of organization Chapter 3. Organizational systems design requirements Chapter 4. The stigmata of unaccountable presence Chapter 5. Organization based on accountably anonymous delegation Chapter 6. Concluding remarks and future work
£42.75
Emerald Publishing Limited Self-Learning and Adaptive Algorithms for
Book SynopsisIn today’s data-driven world, more sophisticated algorithms for data processing are in high demand, mainly when the data cannot be handled with the help of traditional techniques. Self-learning and adaptive algorithms are now widely used by such leading giants that as Google, Tesla, Microsoft, and Facebook in their projects and applications. In this guide designed for researchers and students of computer science, readers will find a resource for how to apply methods that work on real-life problems to their challenging applications, and a go-to work that makes fuzzy clustering issues and aspects clear. Including research relevant to those studying cybernetics, applied mathematics, statistics, engineering, and bioinformatics who are working in the areas of machine learning, artificial intelligence, complex system modeling and analysis, neural networks, and optimization, this is an ideal read for anyone interested in learning more about the fascinating new developments in machine learning.Trade ReviewThis guide explains how to apply methods using systems built by a combination of the neural network approach and fuzzy logic (neuro-fuzzy systems) to solve practical data classification problems in business. It describes methods aimed at handling the main types of uncertainties in data, using adaptive methods of fuzzy clustering; the use of Kohonen maps and their ensembles for fuzzy clustering tasks; and simulation results of these neuro-fuzzy architectures, their learning methods, self-organization, and clustering procedures. -- Annotation ©2019 * (protoview.com) *Table of ContentsIntroduction 1. Review of the Problem Area 2. Adaptive Methods of Fuzzy Clustering 3. Kohonen Maps and their Ensembles for Fuzzy Clustering Tasks 4. Simulation Results and Solutions for Practical Tasks Conclusion
£43.69
Springer London Ltd Graph Theory
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.
£43.70
Imperial College Press New Frontier In Evolutionary Algorithms: Theory
Book SynopsisThis book delivers theoretical and practical knowledge of Genetic Algorithms (GA) for the purpose of practical applications. It provides a methodology for a GA-based search strategy with the integration of several Artificial Life and Artificial Intelligence techniques, such as memetic concepts, swarm intelligence, and foraging strategies. The development of such tools contributes to better optimizing methodologies when addressing tasks from areas such as robotics, financial forecasting, and data mining in bioinformatics.The emphasis of this book is on applicability to the real world. Tasks from application areas - optimization of the trading rule in foreign exchange (FX) and stock prices, economic load dispatch in power system, exit/door placement for evacuation planning, and gene regulatory network inference in bioinformatics - are studied, and the resultant empirical investigations demonstrate how successful the proposed approaches are when solving real-world tasks of great importance.Table of ContentsA Practical Guide to Genetic Algorithms using the Excel Simulator; Real-valued GA and its Variants; The Memetic Computing Approach; Real-world Application of Evolutionary Algorithms.
£57.00
ISTE Ltd and John Wiley & Sons Inc Mesh Generation: Application to Finite Elements
Book SynopsisThe aim of the second edition of this book is to provide a comprehensive survey of the different algorithms and data structures useful for triangulation and meshing construction. In addition, several aspects are given full coverage, such as mesh modification tools, mesh evaluation criteria, mesh optimization, adaptive mesh construction and parallel meshing techniques. This new edition has been comprehensively updated and also includes a new chapter on mobile or deformable meshes.Table of ContentsChapter 1. General definitions. Chapter 2. Basic structures and algorithms. Chapter 3. A comprehensive survey of mesh generation methods. Chapter 4. Algebraic, PDE and multibloc methods. Chapter 5. Quadtree-octree-based methods. Chapter 6. Advancing front technique for mesh generation. Chapter 7. Delaunay-based mesh generation methods. Chapter 8. Other types of mesh generation methods. Chapter 9. Delaunay admissibility, media axis, mid-surface and other applications. Chapter 10. Quadratic forms and metrics. Chapter 11. Differential geometry. Chapter 12. Curve modeling. Chapter 13. Surface modeling. Chapter 14. Surface meshing and re-meshing. Chapter 15. Meshing implicit curves and surfaces. Chapter 16. Mesh modifications. Chapter 17. Mesh optimization. Chapter 18. Surface mesh optimization. Chapter 19. A touch of finite elements. Chapter 20. Mesh adaptation and h-methods. Chapter 21. Mesh adaptation and p or hp-methods. Chapter 22. Mobile or deformable meshes. Chapter 23. Parallel computing and meshing issues.
£204.26
ISTE Ltd and John Wiley & Sons Inc Modeling and Optimization of Air Traffic
Book SynopsisThis book combines the research activities of the authors, both of whom are researchers at Ecole Nationale de l’Aviation Civile (French National School of Civil Aviation), and presents their findings from the last 15 years. Their work uses air transport as its focal point, within the realm of mathematical optimization, looking at real life problems and theoretical models in tandem, and the challenges that accompany studying both approaches. The authors’ research is linked with the attempt to reduce air space congestion in Western Europe, USA and, increasingly, Asia. They do this through studying stochastic optimization (particularly artificial evolution), the sectorization of airspace, route distribution and takeoff slots, and by modeling airspace congestion. Finally, the authors discuss their short, medium and long term research goals. They hope that their work, although related to air transport, will be applied to other fields, such is the transferable nature of mathematical optimization. At the same time, they intend to use other areas of research, such as approximation and statistics to complement their continued inquiry in their own field. Contents 1. Introduction. Part 1. Optimization and Artificial Evolution 2. Optimization: State of the Art. 3. Genetic Algorithms and Improvements. 4. A new concept for Genetic Algorithms based on Order Statistics. Part 2. Applications to Air Traffic Control 5. Air Traffic Control. 6. Contributions to Airspace Sectorization. 7. Contribution to Traffic Assignment. 8. Airspace Congestion Metrics. 9. Conclusion and Future Perspectives. About the Authors Daniel Delahaye works for Ecole Nationale de l’Aviation Civile (French National School of Civil Aviation) in France. Stéphane Puechmorel works for Ecole Nationale de l’Aviation Civile (French National School of Civil Aviation) in France.Table of ContentsIntroduction xi PART 1. OPTIMIZATION AND ARTIFICIAL EVOLUTION 1 Chapter 1. Optimization: State of the Art 3 1.1. Methodological principles in optimization 3 1.1.1. Introduction 3 1.1.2. Modeling 4 1.1.3. Complexity 12 1.1.4. Computation time 13 1.1.5. Conclusion 13 1.2. Optimization algorithms 14 1.2.1. Introduction 14 1.2.2. Linear programming 15 1.2.3. Nonlinear programming (NLP) 16 1.2.4. Local methods subject to constraints 19 1.2.5. Deterministic global methods 21 1.2.6. Stochastic global methods 25 1.2.7. Genetic algorithms 33 1.2.8. Conclusion 34 Chapter 2. Genetic Algorithms and Improvements 37 2.1. General points 37 2.1.1. Introduction 37 2.1.2. Principle of genetic algorithms 39 2.1.3. Coding principles 42 2.1.4. Random generation of the initial population 42 2.1.5. Crossover operators 43 2.1.6. Mutation operators 45 2.1.7. Selection principles 47 2.2. Classic improvements 48 2.2.1. Scaling 49 2.2.2. Sharing 50 2.2.3. Crowding 52 2.2.4. Memetic algorithms 53 2.2.5. Multi-objective genetic algorithms 53 2.3. Our contributions 57 2.3.1. Adaptive clustered sharing 58 2.3.2. Association of genetic algorithms with simulated annealing 60 2.3.3. Parallel genetic algorithms 64 2.4. Conclusion 66 Chapter 3. A New Concept for Genetic Algorithms Based on Order Statistics 67 3.1. Introduction 67 3.2. Order statistics 68 3.3. Estimating the probability that the global optimum belongs to a given domain 71 3.4. Genetic algorithms and order statistics 71 3.4.1. Introduction 71 3.4.2. Coding 72 3.4.3. Recombination operators 73 3.4.4. Evaluation of fitness 75 3.5. Application to test functions 75 3.5.1. Results for the Griewank function 77 3.5.2. Results for the Rosenbrook function 78 3.5.3. Results for the Lennard-Jones function 79 3.6. Conclusion 81 PART 2. APPLICATIONS TO AIR TRAFFIC CONTROL 83 Chapter 4. Air Traffic Control 85 Chapter 5. Contributions to Airspace Sectorization 91 5.1. Introduction 91 5.2. Modeling in 2D 93 5.2.1. Model based on a transportation network 93 5.2.2. Associated complexity 98 5.3. Continuous modeling 99 5.3.1. Principle 99 5.3.2. Chromosome coding 101 5.3.3. Initial population generation principle 101 5.3.4. Crossover operator 101 5.3.5. Mutation operator 103 5.3.6. Calculation and normalization of the fitness function 104 5.3.7. Results 106 5.3.8. Conclusion 110 5.4. Discrete modeling 111 5.4.1. Principle 111 5.4.2. Coding 113 5.4.3. Recombination operators 115 5.4.4. Results 117 5.4.5. Conclusion 119 5.5. Extension 3D 119 5.5.1. Introduction 119 5.5.2. Mathematical modeling 122 5.5.3. Application of artificial evolution to the problem 127 5.5.4. Results 132 5.5.5. Conclusion 135 5.6. Accounting for the dynamic aspect 136 5.6.1. Formalization of objectives and associated mathematical model 136 5.6.2. Optimization using a genetic algorithm: continuous approach 140 5.6.3. Optimization using a genetic algorithm: discrete approach 144 Chapter 6. Contribution to Traffic Assignment 151 6.1. Summary of traffic assignment methods based on transportation network theory 152 6.1.1. Transportation networks 153 6.1.2. Static assignment 155 6.1.3. Dynamic assignment 163 6.2. Other approaches to traffic assignment 167 6.2.1. Temporal extension of the network 167 6.2.2. Optimal control 168 6.2.3. Dynamic programming approaches (ground holding problem) 169 6.2.4. Conclusion 171 6.3. Using artificial evolution in all-or-nothing traffic assignment 173 6.3.1. Mathematical formalization of objectives 173 6.3.2. Coding and operators of the genetic algorithm 176 6.3.3. Introduction of an inter-chromosome distance for sharing 179 6.3.4. Example of results 182 6.3.5. Conclusion 185 6.4. Allocation of routes and slots using artificial evolution 186 6.4.1. System architecture 187 6.4.2. The fitness function 192 6.4.3. Simple genetic algorithm 194 6.5. Modification of the algorithm – adaptive modifications 198 6.5.1. Establishing congestion levels in the chromosome 198 6.5.2. Establishment of trends 200 6.5.3. New coding and biased initial population 203 6.5.4. New crossover operator 203 6.5.5. New mutation operator 204 6.5.6. New results 205 6.5.7. Dynamic bi-allocation 207 6.5.8. Multi-objective approach 210 6.5.9. Conclusion 211 6.6. Sequencing flights for landing 211 6.6.1. Introduction 212 6.6.2. Single runway formulation 213 6.6.3. Modeling using GA 214 6.6.4. Results 217 6.7. Trajectory planning 220 6.7.1. Introduction 220 6.7.2. The light propagation algorithm 222 6.7.3. Approach using genetic algorithms on B-splines 234 6.8. Conclusion 241 Chapter 7. Airspace Congestion Metrics 243 7.1. Introduction 243 7.2. Flow-based approach 248 7.2.1. Mathematical modeling of the control workload 253 7.3. Geometrical approaches 253 7.3.1. Proximity metric 254 7.3.2. Convergence 258 7.3.3. Clusters 263 7.3.4. Grassmannian indicator 265 7.4. Approach based on dynamic systems 268 7.4.1. Linear dynamic systems 268 7.4.2. Spatial extension using nonlinear dynamic systems 273 7.4.3. Spatiotemporal extension using nonlinear dynamic systems 281 7.4.4. Local linear models 285 7.4.5. Stochastic extension 288 Conclusion and Future Perspectives 291 Bibliography 299 Index 327
£132.00
ISTE Ltd and John Wiley & Sons Inc Evolutionary Computation with Biogeography-based
Book SynopsisEvolutionary computation algorithms are employed to minimize functions with large number of variables. Biogeography-based optimization (BBO) is an optimization algorithm that is based on the science of biogeography, which researches the migration patterns of species. These migration paradigms provide the main logic behind BBO. Due to the cross-disciplinary nature of the optimization problems, there is a need to develop multiple approaches to tackle them and to study the theoretical reasoning behind their performance. This book explains the mathematical model of BBO algorithm and its variants created to cope with continuous domain problems (with and without constraints) and combinatorial problems.Table of ContentsChapter 1 The Science of Biogeography 1 1.1 Introduction 1 1.2 Island biogeography 3 1.3 Influence factors for biogeography 6 Chapter 2 Biogeography and Biological Optimization 11 2.1 A mathematical model of biogeography 11 2.2 Biogeography as an optimization process 16 2.3 Biological optimization 19 2.3.1 Genetic algorithms 19 2.3.2 Evolution strategies 20 2.3.3 Particle swarm optimization 21 2.3.4 Artificial bee colony algorithm 22 2.4 Conclusion 23 Chapter 3 A Basic BBO Algorithm 25 3.1 BBO definitions and algorithm 25 3.1.1 Migration 26 3.1.2 Mutation 27 3.1.3 BBO implementation 27 3.2 Differences between BBO and other optimization algorithms 35 3.2.1 BBO and genetic algorithms 35 3.2.2 BBO and other algorithms 36 3.3 Simulations 37 3.4 Conclusion 44 Chapter 4 BBO Extensions 45 4.1 Migration curves 45 4.2 Blended migration 49 4.3 Other approaches to BBO 51 4.4 Applications 56 4.5 Conclusion 59 Chapter 5 BBO as a Markov Process 61 5.1 Markov definitions and notations 61 5.2 Markov model of BBO 72 5.3 BBO convergence 79 5.4 Markov models of BBO extensions 90 5.5 Conclusions 99 Chapter 6 Dynamic System Models of BBO 103 6.1 Basic notation 103 6.2 Dynamic system models of BBO 105 6.3 Applications to benchmark problems 119 6.4 Conclusions 122 Chapter 7 Statistical Mechanics Approximations of BBO 123 7.1 Preliminary foundation 123 7.2 Statistical mechanics model of BBO 128 7.2.1 Migration 128 7.2.2 Mutation 134 7.3 Further discussion 141 7.3.1 Finite population effects 141 7.3.2 Separable fitness functions 142 7.4 Conclusions 143 Chapter 8 BBO for Combinatorial Optimization 145 8.1 Traveling salesman problem 147 8.2 BBO for the TSP 148 8.2.1 Population initialization 148 8.2.2 Migration in the TSP 150 8.2.3 Mutation in the TSP 157 8.2.4 Implementation framework 159 8.3 Graph coloring 163 8.4 Knapsack problem 165 8.5 Conclusion 167 Chapter 9 Constrained BBO 169 9.1 Constrained optimization 170 9.2 Constraint-handling methods 172 9.2.1 Static penalty methods 172 9.2.2 Superiority of feasible points 173 9.2.3 The eclectic evolutionary algorithm 174 9.2.4 Dynamic penalty methods 174 9.2.5 Adaptive penalty methods 176 9.2.6 The niched-penalty approach 177 9.2.7 Stochastic ranking 178 9.2.8 ε-level comparisons 178 9.3 BBO for constrained optimization 179 9.4 Conclusion 185 Chapter 10 BBO in Noisy Environments 187 10.1 Noisy fitness functions 188 10.2 Influence of noise on BBO 190 10.3 BBO with re-sampling 193 10.4 The Kalman BBO 196 10.5 Experimental results 199 10.6 Conclusion 201 Chapter 11 Multi-objective BBO 203 11.1 Multi-objective optimization problems 204 11.2 Multi-objective BBO 211 11.2.1 Vector evaluated BBO 211 11.2.2 Non-dominated sorting BBO 213 11.2.3 Niched Pareto BBO 216 11.2.4 Strength Pareto BBO 218 11.3 Real-world applications 223 11.3.1 Warehouse scheduling model 223 11.3.2 Optimization of warehouse scheduling 229 11.4 Conclusion 231 Chapter 12 Hybrid BBO Algorithms 233 12.1 Opposition-based BBO 234 12.1.1 Opposition definitions and concepts 234 12.1.2 Oppositional BBO 236 12.1.3 Experimental results 238 12.2 BBO with local search 240 12.2.1 Local search methods 240 12.2.2 Simulation results 245 12.3 BBO with other EAs 247 12.3.1 Iteration-level hybridization 247 12.3.2 Algorithm-level hybridization 250 12.3.3 Experimental results 254 12.4 Conclusion 256 Appendices 259 Appendix A Unconstrained Benchmark Functions 261 Appendix B Constrained Benchmark Functions 265 Appendix C Multi-objective Benchmark Functions 289 Bibliography 309 Index 325
£125.06
College Publications Conception Et Analyse Des Programmes Purement Fonctionnels Deuxieme Edition
£19.00
College Publications Introduction to Propositional Satisfiability
£15.20
Springer London Ltd Ontological Engineering: with examples from the areas of Knowledge Management, e-Commerce and the Semantic Web. First Edition
Ontological Engineering refers to the set of activities that concern the ontology development process, the ontology life cycle, the methods and methodologies for building ontologies, and the tool suites and languages that support them. During the last decade, increasing attention has been focused on ontologies and Ontological Engineering. Ontologies are now widely used in Knowledge Engineering, Artificial Intelligence and Computer Science; in applications related to knowledge management, natural language processing, e-commerce, intelligent integration information, information retrieval, integration of databases, b- informatics, and education; and in new emerging fields like the Semantic Web. Primary goals of this book are to acquaint students, researchers and developers of information systems with the basic concepts and major issues of Ontological Engineering, as well as to make ontologies more understandable to those computer science engineers that integrate ontologies into their information systems. We have paid special attention to the influence that ontologies have on the Semantic Web. Pointers to the Semantic Web appear in all the chapters, but specially in the chapter on ontology languages and tools.
£97.49
New Age International (UK) Ltd A Practical Approach to Data Structures and
Book Synopsis
£38.00
Apple Academic Press Inc. Algorithmic Techniques for the Polymer Sciences
Book SynopsisThis new book—the first of its kind—examines the use of algorithmic techniques to compress random and non-random sequential strings found in chains of polymers. The book is an introduction to algorithmic complexity. Examples taken from current research in the polymer sciences are used for compression of like-natured properties as found on a chain of polymers. Both theory and applied aspects of algorithmic compression are reviewed. A description of the types of polymers and their uses is followed by a chapter on various types of compression systems that can be used to compress polymer chains into manageable units. The work is intended for graduate and postgraduate university students in the physical sciences and engineering.Table of ContentsIntroduction. Literature Review. Polymers. Compression of Data. Natural Language Compression. Formal Language Compression. Types of Compression Programs. Algorithmic Compression. Chemical Formulas. Fischer Projection. Compression of Polymers. Line Notation Systems and Compression. Current Trends in Research. Big Data. Modeling Complexity in Molecular Systems. Feedback Systems for Nontraditional Medicines: A Case for the Signal Flow Diagram. Chromatic Aspects of the Signal Flow Diagram. Junction Graphs. Embedded Symbol Notation Diagrams and Embedded Symbol Notation Matrix Diagrams. Feedback Theory: Properties of Signal Flow Graphs (From Appendix L). An Overview of Signal Flow. A Theory on Neurological Systems: Part I and Part II. A Theoretical Model of Feedback in Pharmacology Using Signal Flow Diagrams. Appendixes.
£108.00
Pearson Education Mahout in Action
Book Synopsis
£39.74
Morgan & Claypool Publishers The Sparse Fourier Transform
Book SynopsisThe Fourier transform is one of the most fundamental tools for computing the frequency representation of signals. It plays a central role in signal processing, communications, audio and video compression, medical imaging, genomics, astronomy, as well as many other areas. Because of its widespread use, fast algorithms for computing the Fourier transform can benefit a large number of applications. The fastest algorithm for computing the Fourier transform is the Fast Fourier Transform (FFT), which runs in near-linear time making it an indispensable tool for many applications. However, today, the runtime of the FFT algorithm is no longer fast enough especially for big data problems where each dataset can be few terabytes. Hence, faster algorithms that run in sublinear time, i.e., do not even sample all the data points, have become necessary.This book addresses the above problem by developing the Sparse Fourier Transform algorithms and building practical systems that use these algorithms to solve key problems in six different applications: wireless networks; mobile systems; computer graphics; medical imaging; biochemistry; and digital circuits.This is a revised version of the thesis that won the 2016 ACM Doctoral Dissertation Award.Table of Contents Preface 1. Introduction PART I: THEORY OF THE SPARSE FOURIER TRANSFORM 2. Preliminaries 3. Simple and Practical Algorithm 4. Optimizing Runtime Complexity 5. Optimizing Sample Complexity 6. Numerical Evaluation PART II: APPLICATIONS OF THE SPARSE FOURIER TRANSFORM 7. GHz-Wide Spectrum Sensing and Decoding 8. Faster GPS Synchronization 9. Light Field Reconstruction Using Continuous Fourier Sparsity 10. Fast In-Vivo MRS Acquisition with Artifact Suppression 11. Fast Multi-Dimensional NMR Acquisition and Processing 12. Conclusion
£68.00
Morgan & Claypool Publishers The Sparse Fourier Transform
Book SynopsisThe Fourier transform is one of the most fundamental tools for computing the frequency representation of signals. It plays a central role in signal processing, communications, audio and video compression, medical imaging, genomics, astronomy, as well as many other areas. Because of its widespread use, fast algorithms for computing the Fourier transform can benefit a large number of applications. The fastest algorithm for computing the Fourier transform is the Fast Fourier Transform (FFT), which runs in near-linear time making it an indispensable tool for many applications. However, today, the runtime of the FFT algorithm is no longer fast enough especially for big data problems where each dataset can be few terabytes. Hence, faster algorithms that run in sublinear time, i.e., do not even sample all the data points, have become necessary.This book addresses the above problem by developing the Sparse Fourier Transform algorithms and building practical systems that use these algorithms to solve key problems in six different applications: wireless networks; mobile systems; computer graphics; medical imaging; biochemistry; and digital circuits.This is a revised version of the thesis that won the 2016 ACM Doctoral Dissertation Award.Table of Contents Preface 1. Introduction PART I: THEORY OF THE SPARSE FOURIER TRANSFORM 2. Preliminaries 3. Simple and Practical Algorithm 4. Optimizing Runtime Complexity 5. Optimizing Sample Complexity 6. Numerical Evaluation PART II: APPLICATIONS OF THE SPARSE FOURIER TRANSFORM 7. GHz-Wide Spectrum Sensing and Decoding 8. Faster GPS Synchronization 9. Light Field Reconstruction Using Continuous Fourier Sparsity 10. Fast In-Vivo MRS Acquisition with Artifact Suppression 11. Fast Multi-Dimensional NMR Acquisition and Processing 12. Conclusion
£79.20
Morgan & Claypool Publishers Shared-Memory Parallelism Can Be Simple, Fast,
Book SynopsisParallelism is the key to achieving high performance in computing. However, writing efficient and scalable parallel programs is notoriously difficult, and often requires significant expertise. To address this challenge, it is crucial to provide programmers with high-level tools to enable them to develop solutions easily, and at the same time emphasize the theoretical and practical aspects of algorithm design to allow the solutions developed to run efficiently under many different settings. This thesis addresses this challenge using a three-pronged approach consisting of the design of shared-memory programming techniques, frameworks, and algorithms for important problems in computing. The thesis provides evidence that with appropriate programming techniques, frameworks, and algorithms, shared-memory programs can be simple, fast, and scalable, both in theory and in practice. The results developed in this thesis serve to ease the transition into the multicore era.The first part of this thesis introduces tools and techniques for deterministic parallel programming, including means for encapsulating nondeterminism via powerful commutative building blocks, as well as a novel framework for executing sequential iterative loops in parallel, which lead to deterministic parallel algorithms that are efficient both in theory and in practice. The second part of this thesis introduces Ligra, the first high-level shared memory framework for parallel graph traversal algorithms. The framework allows programmers to express graph traversal algorithms using very short and concise code, delivers performance competitive with that of highly-optimized code, and is up to orders of magnitude faster than existing systems designed for distributed memory. This part of the thesis also introduces Ligra , which extends Ligra with graph compression techniques to reduce space usage and improve parallel performance at the same time, and is also the first graph processing system to support in-memory graph compression.The third and fourth parts of this thesis bridge the gap between theory and practice in parallel algorithm design by introducing the first algorithms for a variety of important problems on graphs and strings that are efficient both in theory and in practice. For example, the thesis develops the first linear-work and polylogarithmic-depth algorithms for suffix tree construction and graph connectivity that are also practical, as well as a work-efficient, polylogarithmic-depth, and cache-efficient shared-memory algorithm for triangle computations that achieves a 2–5x speedup over the best existing algorithms on 40 cores.This is a revised version of the thesis that won the 2015 ACM Doctoral Dissertation Award.Table of Contents Introduction Preliminaries and Notation Programming Techniques for Deterministic Parallelism Internally Deterministic Parallelism: Techniques and Algorithms Deterministic Parallelism in Sequential Iterative Algorithms A Deterministic Phase-Concurrent Parallel Hash Table Priority Updates: A Contention-Reducing Primitive for Deterministic Programming Large-Scale Shared-Memory Graph Analytics Ligra: A Lightweight Graph Processing Framework for Shared Memory Ligra : Adding Compression to Ligra Parallel Graph Algorithms Linear-Work Parallel Graph Connectivity Parallel and Cache-Oblivious Triangle Computations Parallel String Algorithms Parallel Cartesian Tree and Suffix Tree Construction Parallel Computation of Longest Common Prefixes Parallel Lempel-Ziv Factorization Parallel Wavelet Tree Construction Conclusion and Future Work Bibliography
£75.65
Morgan & Claypool Publishers Shared-Memory Parallelism Can Be Simple, Fast,
Book SynopsisParallelism is the key to achieving high performance in computing. However, writing efficient and scalable parallel programs is notoriously difficult, and often requires significant expertise. To address this challenge, it is crucial to provide programmers with high-level tools to enable them to develop solutions easily, and at the same time emphasize the theoretical and practical aspects of algorithm design to allow the solutions developed to run efficiently under many different settings. This thesis addresses this challenge using a three-pronged approach consisting of the design of shared-memory programming techniques, frameworks, and algorithms for important problems in computing. The thesis provides evidence that with appropriate programming techniques, frameworks, and algorithms, shared-memory programs can be simple, fast, and scalable, both in theory and in practice. The results developed in this thesis serve to ease the transition into the multicore era.The first part of this thesis introduces tools and techniques for deterministic parallel programming, including means for encapsulating nondeterminism via powerful commutative building blocks, as well as a novel framework for executing sequential iterative loops in parallel, which lead to deterministic parallel algorithms that are efficient both in theory and in practice. The second part of this thesis introduces Ligra, the first high-level shared memory framework for parallel graph traversal algorithms. The framework allows programmers to express graph traversal algorithms using very short and concise code, delivers performance competitive with that of highly-optimized code, and is up to orders of magnitude faster than existing systems designed for distributed memory. This part of the thesis also introduces Ligra , which extends Ligra with graph compression techniques to reduce space usage and improve parallel performance at the same time, and is also the first graph processing system to support in-memory graph compression.The third and fourth parts of this thesis bridge the gap between theory and practice in parallel algorithm design by introducing the first algorithms for a variety of important problems on graphs and strings that are efficient both in theory and in practice. For example, the thesis develops the first linear-work and polylogarithmic-depth algorithms for suffix tree construction and graph connectivity that are also practical, as well as a work-efficient, polylogarithmic-depth, and cache-efficient shared-memory algorithm for triangle computations that achieves a 2–5x speedup over the best existing algorithms on 40 cores.This is a revised version of the thesis that won the 2015 ACM Doctoral Dissertation Award.Table of Contents Introduction Preliminaries and Notation Programming Techniques for Deterministic Parallelism Internally Deterministic Parallelism: Techniques and Algorithms Deterministic Parallelism in Sequential Iterative Algorithms A Deterministic Phase-Concurrent Parallel Hash Table Priority Updates: A Contention-Reducing Primitive for Deterministic Programming Large-Scale Shared-Memory Graph Analytics Ligra: A Lightweight Graph Processing Framework for Shared Memory Ligra : Adding Compression to Ligra Parallel Graph Algorithms Linear-Work Parallel Graph Connectivity Parallel and Cache-Oblivious Triangle Computations Parallel String Algorithms Parallel Cartesian Tree and Suffix Tree Construction Parallel Computation of Longest Common Prefixes Parallel Lempel-Ziv Factorization Parallel Wavelet Tree Construction Conclusion and Future Work Bibliography
£89.25
Springer Nature Switzerland AG Core Data Analysis: Summarization, Correlation,
Book SynopsisThis text examines the goals of data analysis with respect to enhancing knowledge, and identifies data summarization and correlation analysis as the core issues. Data summarization, both quantitative and categorical, is treated within the encoder-decoder paradigm bringing forward a number of mathematically supported insights into the methods and relations between them. Two Chapters describe methods for categorical summarization: partitioning, divisive clustering and separate cluster finding and another explain the methods for quantitative summarization, Principal Component Analysis and PageRank. Features:· An in-depth presentation of K-means partitioning including a corresponding Pythagorean decomposition of the data scatter. · Advice regarding such issues as clustering of categorical and mixed scale data, similarity and network data, interpretation aids, anomalous clusters, the number of clusters, etc.· Thorough attention to data-driven modelling including a number of mathematically stated relations between statistical and geometrical concepts including those between goodness-of-fit criteria for decision trees and data standardization, similarity and consensus clustering, modularity clustering and uniform partitioning.New edition highlights: · Inclusion of ranking issues such as Google PageRank, linear stratification and tied rankings median, consensus clustering, semi-average clustering, one-cluster clustering· Restructured to make the logics more straightforward and sections self-containedCore Data Analysis: Summarization, Correlation and Visualization is aimed at those who are eager to participate in developing the field as well as appealing to novices and practitioners. Trade Review“This book provides a clear overview of the data analysis process, the different types of statistical techniques employed for data analysis, and their role and purpose. … There is good use of a variety of examples to demonstrate how the different techniques are applied in practice. The book’s main purpose would be as a textbook for undergraduate students, or a reference book for data analysts.” (Mark Taylor, Computing Reviews, May 5, 2022)Table of Contents
£49.49
