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Author: Imre Csiszár
Publisher: Now Publishers Inc
ISBN: 9781933019055
Category : Computers
Languages : en
Pages : 128
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Book Description
Information Theory and Statistics: A Tutorial is concerned with applications of information theory concepts in statistics, in the finite alphabet setting. The topics covered include large deviations, hypothesis testing, maximum likelihood estimation in exponential families, analysis of contingency tables, and iterative algorithms with an "information geometry" background. Also, an introduction is provided to the theory of universal coding, and to statistical inference via the minimum description length principle motivated by that theory. The tutorial does not assume the reader has an in-depth knowledge of Information Theory or statistics. As such, Information Theory and Statistics: A Tutorial, is an excellent introductory text to this highly-important topic in mathematics, computer science and electrical engineering. It provides both students and researchers with an invaluable resource to quickly get up to speed in the field.
Author: Imre Csiszár
Publisher: Now Publishers Inc
ISBN: 9781933019055
Category : Computers
Languages : en
Pages : 128
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Book Description
Information Theory and Statistics: A Tutorial is concerned with applications of information theory concepts in statistics, in the finite alphabet setting. The topics covered include large deviations, hypothesis testing, maximum likelihood estimation in exponential families, analysis of contingency tables, and iterative algorithms with an "information geometry" background. Also, an introduction is provided to the theory of universal coding, and to statistical inference via the minimum description length principle motivated by that theory. The tutorial does not assume the reader has an in-depth knowledge of Information Theory or statistics. As such, Information Theory and Statistics: A Tutorial, is an excellent introductory text to this highly-important topic in mathematics, computer science and electrical engineering. It provides both students and researchers with an invaluable resource to quickly get up to speed in the field.
Author: Solomon Kullback
Publisher: Courier Corporation
ISBN: 0486142043
Category : Mathematics
Languages : en
Pages : 436
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Book Description
Highly useful text studies logarithmic measures of information and their application to testing statistical hypotheses. Includes numerous worked examples and problems. References. Glossary. Appendix. 1968 2nd, revised edition.
Author: Robert B. Ash
Publisher: Halsted Press
ISBN:
Category : Computers
Languages : en
Pages : 360
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Book Description
Author: Frank Emmert-Streib
Publisher: Springer Science & Business Media
ISBN: 0387848150
Category : Computers
Languages : en
Pages : 443
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Book Description
This interdisciplinary text offers theoretical and practical results of information theoretic methods used in statistical learning. It presents a comprehensive overview of the many different methods that have been developed in numerous contexts.
Author: Fady Alajaji
Publisher: Springer
ISBN: 9811080011
Category : Mathematics
Languages : en
Pages : 333
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Book Description
This book presents a succinct and mathematically rigorous treatment of the main pillars of Shannon’s information theory, discussing the fundamental concepts and indispensable results of Shannon’s mathematical theory of communications. It includes five meticulously written core chapters (with accompanying problems), emphasizing the key topics of information measures; lossless and lossy data compression; channel coding; and joint source-channel coding for single-user (point-to-point) communications systems. It also features two appendices covering necessary background material in real analysis and in probability theory and stochastic processes. The book is ideal for a one-semester foundational course on information theory for senior undergraduate and entry-level graduate students in mathematics, statistics, engineering, and computing and information sciences. A comprehensive instructor’s solutions manual is available.
Author: D.C. Hankerson
Publisher: CRC Press
ISBN: 9781584883135
Category : Mathematics
Languages : en
Pages : 394
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Book Description
An effective blend of carefully explained theory and practical applications, this text imparts the fundamentals of both information theory and data compression. Although the two topics are related, this unique text allows either topic to be presented independently, and it was specifically designed so that the data compression section requires no prior knowledge of information theory. The treatment of information theory, while theoretical and abstract, is quite elementary, making this text less daunting than many others. After presenting the fundamental definitions and results of the theory, the authors then apply the theory to memoryless, discrete channels with zeroth-order, one-state sources. The chapters on data compression acquaint students with a myriad of lossless compression methods and then introduce two lossy compression methods. Students emerge from this study competent in a wide range of techniques. The authors' presentation is highly practical but includes some important proofs, either in the text or in the exercises, so instructors can, if they choose, place more emphasis on the mathematics. Introduction to Information Theory and Data Compression, Second Edition is ideally suited for an upper-level or graduate course for students in mathematics, engineering, and computer science. Features: Expanded discussion of the historical and theoretical basis of information theory that builds a firm, intuitive grasp of the subject Reorganization of theoretical results along with new exercises, ranging from the routine to the more difficult, that reinforce students' ability to apply the definitions and results in specific situations. Simplified treatment of the algorithm(s) of Gallager and Knuth Discussion of the information rate of a code and the trade-off between error correction and information rate Treatment of probabilistic finite state source automata, including basic results, examples, references, and exercises Octave and MATLAB image compression codes included in an appendix for use with the exercises and projects involving transform methods Supplementary materials, including software, available for download from the authors' Web site at www.dms.auburn.edu/compression
Author: A. M. Mathai
Publisher: John Wiley & Sons
ISBN:
Category : Mathematics
Languages : en
Pages : 162
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Book Description
The concept of uncertainty. The concept of directed divergence. The concept of inaccuracy. Some basic statistical concepts and their characterizations. Some other measures and inequalities.
Author: Klaus Krippendorff
Publisher: SAGE
ISBN: 9780803921320
Category : Computers
Languages : en
Pages : 100
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Book Description
Information theory always has the dual appeal of bringing important concepts to the study of communication in society, and of providing a calculus for information flows within systems. This book introduces readers to basic concepts of information theory, extending its original linear conception of communication to many variables, networks, and higher-order interactions (including loops) and developing it into a method for analyzing qualitative data. It elaborates on the algebra of entropy and information, shows how complex models of data are constructed and tested, describes algorithms for exploring multivariate structures using such models, and gives illustrative applications of these techniques. The book is designed as a text but it can also serve as a handbook for social researchers and systems theorists with an interest in communication.
Author: Solomon W. Golomb
Publisher: Springer Science & Business Media
ISBN: 1475723199
Category : Technology & Engineering
Languages : en
Pages : 442
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Book Description
Basic Concepts in Information Theory and Coding is an outgrowth of a one semester introductory course that has been taught at the University of Southern California since the mid-1960s. Lecture notes from that course have evolved in response to student reaction, new technological and theoretical develop ments, and the insights of faculty members who have taught the course (in cluding the three of us). In presenting this material, we have made it accessible to a broad audience by limiting prerequisites to basic calculus and the ele mentary concepts of discrete probability theory. To keep the material suitable for a one-semester course, we have limited its scope to discrete information theory and a general discussion of coding theory without detailed treatment of algorithms for encoding and decoding for various specific code classes. Readers will find that this book offers an unusually thorough treatment of noiseless self-synchronizing codes, as well as the advantage of problem sections that have been honed by reactions and interactions of several gen erations of bright students, while Agent 00111 provides a context for the discussion of abstract concepts.
Author: JV Stone
Publisher: Sebtel Press
ISBN: 0956372856
Category : Business & Economics
Languages : en
Pages : 243
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Book Description
Originally developed by Claude Shannon in the 1940s, information theory laid the foundations for the digital revolution, and is now an essential tool in telecommunications, genetics, linguistics, brain sciences, and deep space communication. In this richly illustrated book, accessible examples are used to introduce information theory in terms of everyday games like ‘20 questions’ before more advanced topics are explored. Online MatLab and Python computer programs provide hands-on experience of information theory in action, and PowerPoint slides give support for teaching. Written in an informal style, with a comprehensive glossary and tutorial appendices, this text is an ideal primer for novices who wish to learn the essential principles and applications of information theory.
