Abstract Methods In Information Theory

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Abstract Methods in Information Theory

Author : Yichir Kakihara
Publisher : World Scientific
ISBN 13 : 9789810237110
Total Pages : 272 pages
Book Rating : 4.2/5 (371 download)

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Book Synopsis Abstract Methods in Information Theory by : Yichir Kakihara

Download or read book Abstract Methods in Information Theory written by Yichir Kakihara and published by World Scientific. This book was released on 1999 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information Theory is studied from the following view points: (1) the theory of entropy as amount of information; (2) the mathematical structure of information sources (probability measures); and (3) the theory of information channels. Shannon entropy and Kolmogorov-Sinai entropy are defined and their basic properties are examined, where the latter entropy is extended to be a linear functional on a certain set of measures. Ergodic and mixing properties of stationary sources are studied as well as AMS (asymptotically mean stationary) sources. The main purpose of this book is to present information channels in the environment of real and functional analysis as well as probability theory. Ergodic channels are characterized in various manners. Mixing and AMS channels are also considered in detail with some illustrations. A few other aspects of information channels including measurability, approximation and noncommutative extensions, are also discussed.

Abstract Methods In Information Theory (Second Edition)

Author : Yuichiro Kakihara
Publisher : World Scientific
ISBN 13 : 9814759252
Total Pages : 413 pages
Book Rating : 4.8/5 (147 download)

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Book Synopsis Abstract Methods In Information Theory (Second Edition) by : Yuichiro Kakihara

Download or read book Abstract Methods In Information Theory (Second Edition) written by Yuichiro Kakihara and published by World Scientific. This book was released on 2016-06-09 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information Theory is studied from the following points of view: (1) the theory of entropy as amount of information; (2) the mathematical structure of information sources (probability measures); and (3) the theory of information channels. Shannon entropy and Kolmogorov-Sinai entropy are defined and their basic properties are examined, where the latter entropy is extended to be a linear functional on a certain set of measures. Ergodic and mixing properties of stationary sources are studied as well as AMS (asymptotically mean stationary) sources.The main purpose of this book is to present information channels in the environment of functional analysis and operator theory as well as probability theory. Ergodic, mixing, and AMS channels are also considered in detail with some illustrations. In this second edition, channel operators are studied in many aspects, which generalize ordinary channels. Also Gaussian channels are considered in detail together with Gaussian measures on a Hilbert space. The Special Topics chapter deals with features such as generalized capacity, channels with an intermediate noncommutative system, and von Neumann algebra method for channels. Finally, quantum (noncommutative) information channels are examined in an independent chapter, which may be regarded as an introduction to quantum information theory. Von Neumann entropy is introduced and its generalization to a C*-algebra setting is given. Basic results on quantum channels and entropy transmission are also considered.

Information Theory and Network Coding

Author : Raymond W. Yeung
Publisher : Springer Science & Business Media
ISBN 13 : 0387792341
Total Pages : 592 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Information Theory and Network Coding by : Raymond W. Yeung

Download or read book Information Theory and Network Coding written by Raymond W. Yeung and published by Springer Science & Business Media. This book was released on 2008-08-28 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an evolution from my book A First Course in Information Theory published in 2002 when network coding was still at its infancy. The last few years have witnessed the rapid development of network coding into a research ?eld of its own in information science. With its root in infor- tion theory, network coding has not only brought about a paradigm shift in network communications at large, but also had signi?cant in?uence on such speci?c research ?elds as coding theory, networking, switching, wireless c- munications,distributeddatastorage,cryptography,andoptimizationtheory. While new applications of network coding keep emerging, the fundamental - sults that lay the foundation of the subject are more or less mature. One of the main goals of this book therefore is to present these results in a unifying and coherent manner. While the previous book focused only on information theory for discrete random variables, the current book contains two new chapters on information theory for continuous random variables, namely the chapter on di?erential entropy and the chapter on continuous-valued channels. With these topics included, the book becomes more comprehensive and is more suitable to be used as a textbook for a course in an electrical engineering department.

Information Theory, Inference and Learning Algorithms

Author : David J. C. MacKay
Publisher : Cambridge University Press
ISBN 13 : 9780521642989
Total Pages : 694 pages
Book Rating : 4.6/5 (429 download)

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Book Synopsis Information Theory, Inference and Learning Algorithms by : David J. C. MacKay

Download or read book Information Theory, Inference and Learning Algorithms written by David J. C. MacKay and published by Cambridge University Press. This book was released on 2003-09-25 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.

Information Theory and Statistics

Author : Imre Csiszár
Publisher : Now Publishers Inc
ISBN 13 : 9781933019055
Total Pages : 128 pages
Book Rating : 4.0/5 (19 download)

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Book Synopsis Information Theory and Statistics by : Imre Csiszár

Download or read book Information Theory and Statistics written by Imre Csiszár and published by Now Publishers Inc. This book was released on 2004 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Coding and Information Theory

Author : Richard Wesley Hamming
Publisher : Prentice Hall
ISBN 13 :
Total Pages : 280 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Coding and Information Theory by : Richard Wesley Hamming

Download or read book Coding and Information Theory written by Richard Wesley Hamming and published by Prentice Hall. This book was released on 1986 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on both theory and practical applications, this volume combines in a natural way the two major aspects of information representation--representation for storage (coding theory) and representation for transmission (information theory).

Information Theory and the Central Limit Theorem

Author : Oliver Thomas Johnson
Publisher : World Scientific
ISBN 13 : 1860944736
Total Pages : 224 pages
Book Rating : 4.8/5 (69 download)

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Book Synopsis Information Theory and the Central Limit Theorem by : Oliver Thomas Johnson

Download or read book Information Theory and the Central Limit Theorem written by Oliver Thomas Johnson and published by World Scientific. This book was released on 2004 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive description of a new method of proving the central limit theorem, through the use of apparently unrelated results from information theory. It gives a basic introduction to the concepts of entropy and Fisher information, and collects together standard results concerning their behaviour. It brings together results from a number of research papers as well as unpublished material, showing how the techniques can give a unified view of limit theorems.

Coding and Information Theory

Author : Steven Roman
Publisher : Springer Science & Business Media
ISBN 13 : 9780387978123
Total Pages : 520 pages
Book Rating : 4.9/5 (781 download)

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Book Synopsis Coding and Information Theory by : Steven Roman

Download or read book Coding and Information Theory written by Steven Roman and published by Springer Science & Business Media. This book was released on 1992-06-04 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an introduction to information and coding theory at the graduate or advanced undergraduate level. It assumes a basic knowledge of probability and modern algebra, but is otherwise self- contained. The intent is to describe as clearly as possible the fundamental issues involved in these subjects, rather than covering all aspects in an encyclopedic fashion. The first quarter of the book is devoted to information theory, including a proof of Shannon's famous Noisy Coding Theorem. The remainder of the book is devoted to coding theory and is independent of the information theory portion of the book. After a brief discussion of general families of codes, the author discusses linear codes (including the Hamming, Golary, the Reed-Muller codes), finite fields, and cyclic codes (including the BCH, Reed-Solomon, Justesen, Goppa, and Quadratic Residue codes). An appendix reviews relevant topics from modern algebra.

Technical Abstract Bulletin

Author : Defense Documentation Center (U.S.)
Publisher :
ISBN 13 :
Total Pages : 1032 pages
Book Rating : 4.:/5 (5 download)

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Book Synopsis Technical Abstract Bulletin by : Defense Documentation Center (U.S.)

Download or read book Technical Abstract Bulletin written by Defense Documentation Center (U.S.) and published by . This book was released on 1963 with total page 1032 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Concentration of Measure Inequalities in Information Theory, Communications, and Coding

Author : Maxim Raginsky
Publisher :
ISBN 13 : 9781601989062
Total Pages : 256 pages
Book Rating : 4.9/5 (89 download)

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Book Synopsis Concentration of Measure Inequalities in Information Theory, Communications, and Coding by : Maxim Raginsky

Download or read book Concentration of Measure Inequalities in Information Theory, Communications, and Coding written by Maxim Raginsky and published by . This book was released on 2014 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concentration of Measure Inequalities in Information Theory, Communications, and Coding focuses on some of the key modern mathematical tools that are used for the derivation of concentration inequalities, on their links to information theory, and on their various applications to communications and coding.

Information Theory

Author : Defense Documentation Center (U.S.)
Publisher :
ISBN 13 :
Total Pages : 72 pages
Book Rating : 4.:/5 (319 download)

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Book Synopsis Information Theory by : Defense Documentation Center (U.S.)

Download or read book Information Theory written by Defense Documentation Center (U.S.) and published by . This book was released on 1962 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Introduction to Information Theory and Data Compression, Second Edition

Author : D.C. Hankerson
Publisher : CRC Press
ISBN 13 : 9781584883135
Total Pages : 394 pages
Book Rating : 4.8/5 (831 download)

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Book Synopsis Introduction to Information Theory and Data Compression, Second Edition by : D.C. Hankerson

Download or read book Introduction to Information Theory and Data Compression, Second Edition written by D.C. Hankerson and published by CRC Press. This book was released on 2003-02-26 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Information Theory and Coding - Solved Problems

Author : Predrag Ivaniš
Publisher : Springer
ISBN 13 : 3319493701
Total Pages : 517 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Information Theory and Coding - Solved Problems by : Predrag Ivaniš

Download or read book Information Theory and Coding - Solved Problems written by Predrag Ivaniš and published by Springer. This book was released on 2016-11-29 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is offers a comprehensive overview of information theory and error control coding, using a different approach then in existed literature. The chapters are organized according to the Shannon system model, where one block affects the others. A relatively brief theoretical introduction is provided at the beginning of every chapter, including a few additional examples and explanations, but without any proofs. And a short overview of some aspects of abstract algebra is given at the end of the corresponding chapters. The characteristic complex examples with a lot of illustrations and tables are chosen to provide detailed insights into the nature of the problem. Some limiting cases are presented to illustrate the connections with the theoretical bounds. The numerical values are carefully selected to provide in-depth explanations of the described algorithms. Although the examples in the different chapters can be considered separately, they are mutually connected and the conclusions for one considered problem relate to the others in the book.

Rule Based Systems for Big Data

Author : Han Liu
Publisher : Springer
ISBN 13 : 3319236962
Total Pages : 127 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Rule Based Systems for Big Data by : Han Liu

Download or read book Rule Based Systems for Big Data written by Han Liu and published by Springer. This book was released on 2015-09-09 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.

Information Theory in Computer Vision and Pattern Recognition

Author : Francisco Escolano Ruiz
Publisher : Springer Science & Business Media
ISBN 13 : 1848822979
Total Pages : 375 pages
Book Rating : 4.8/5 (488 download)

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Book Synopsis Information Theory in Computer Vision and Pattern Recognition by : Francisco Escolano Ruiz

Download or read book Information Theory in Computer Vision and Pattern Recognition written by Francisco Escolano Ruiz and published by Springer Science & Business Media. This book was released on 2009-07-14 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information theory has proved to be effective for solving many computer vision and pattern recognition (CVPR) problems (such as image matching, clustering and segmentation, saliency detection, feature selection, optimal classifier design and many others). Nowadays, researchers are widely bringing information theory elements to the CVPR arena. Among these elements there are measures (entropy, mutual information...), principles (maximum entropy, minimax entropy...) and theories (rate distortion theory, method of types...). This book explores and introduces the latter elements through an incremental complexity approach at the same time where CVPR problems are formulated and the most representative algorithms are presented. Interesting connections between information theory principles when applied to different problems are highlighted, seeking a comprehensive research roadmap. The result is a novel tool both for CVPR and machine learning researchers, and contributes to a cross-fertilization of both areas.

A First Course in Information Theory

Author : Raymond W. Yeung
Publisher : Springer Science & Business Media
ISBN 13 : 1441986081
Total Pages : 426 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis A First Course in Information Theory by : Raymond W. Yeung

Download or read book A First Course in Information Theory written by Raymond W. Yeung and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an up-to-date introduction to information theory. In addition to the classical topics discussed, it provides the first comprehensive treatment of the theory of I-Measure, network coding theory, Shannon and non-Shannon type information inequalities, and a relation between entropy and group theory. ITIP, a software package for proving information inequalities, is also included. With a large number of examples, illustrations, and original problems, this book is excellent as a textbook or reference book for a senior or graduate level course on the subject, as well as a reference for researchers in related fields.

Fundamentals of Information Theory and Coding Design

Author : Roberto Togneri
Publisher : CRC Press
ISBN 13 : 0203998103
Total Pages : 394 pages
Book Rating : 4.2/5 (39 download)

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Book Synopsis Fundamentals of Information Theory and Coding Design by : Roberto Togneri

Download or read book Fundamentals of Information Theory and Coding Design written by Roberto Togneri and published by CRC Press. This book was released on 2003-01-13 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Books on information theory and coding have proliferated over the last few years, but few succeed in covering the fundamentals without losing students in mathematical abstraction. Even fewer build the essential theoretical framework when presenting algorithms and implementation details of modern coding systems. Without abandoning the theoret