A First Course in Information Theory

A First Course in Information Theory PDF Author: Raymond W. Yeung
Publisher: Springer Science & Business Media
ISBN: 9780306467912
Category : Computers
Languages : en
Pages : 440

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Book Description
An introduction to information theory for discrete random variables. Classical topics and fundamental tools are presented along with three selected advanced topics. Yeung (Chinese U. of Hong Kong) presents chapters on information measures, zero-error data compression, weak and strong typicality, the I-measure, Markov structures, channel capacity, rate distortion theory, Blahut-Arimoto algorithms, information inequalities, and Shannon-type inequalities. The advanced topics included are single-source network coding, multi-source network coding, and entropy and groups. Annotation copyrighted by Book News, Inc., Portland, OR.

A First Course in Information Theory

A First Course in Information Theory PDF Author: Raymond W. Yeung
Publisher: Springer Science & Business Media
ISBN: 9780306467912
Category : Computers
Languages : en
Pages : 440

Get Book Here

Book Description
An introduction to information theory for discrete random variables. Classical topics and fundamental tools are presented along with three selected advanced topics. Yeung (Chinese U. of Hong Kong) presents chapters on information measures, zero-error data compression, weak and strong typicality, the I-measure, Markov structures, channel capacity, rate distortion theory, Blahut-Arimoto algorithms, information inequalities, and Shannon-type inequalities. The advanced topics included are single-source network coding, multi-source network coding, and entropy and groups. Annotation copyrighted by Book News, Inc., Portland, OR.

A First Course in Information Theory

A First Course in Information Theory PDF Author: Raymond W. Yeung
Publisher: Springer Science & Business Media
ISBN: 1441986081
Category : Technology & Engineering
Languages : en
Pages : 426

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Book Description
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.

A First Course in Information Theory

A First Course in Information Theory PDF Author: Raymond W. Yeung
Publisher: Springer
ISBN: 9781461346456
Category : Technology & Engineering
Languages : en
Pages : 0

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Book Description
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.

Information Theory and Network Coding

Information Theory and Network Coding PDF Author: Raymond W. Yeung
Publisher: Springer Science & Business Media
ISBN: 0387792333
Category : Computers
Languages : en
Pages : 592

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Book Description
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.

Introduction to Coding and Information Theory

Introduction to Coding and Information Theory PDF Author: Steven Roman
Publisher: Springer Science & Business Media
ISBN: 9780387947044
Category : Computers
Languages : en
Pages : 344

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Book Description
This book is intended to introduce coding theory and information theory to undergraduate students of mathematics and computer science. It begins with a review of probablity theory as applied to finite sample spaces and a general introduction to the nature and types of codes. The two subsequent chapters discuss information theory: efficiency of codes, the entropy of information sources, and Shannon's Noiseless Coding Theorem. The remaining three chapters deal with coding theory: communication channels, decoding in the presence of errors, the general theory of linear codes, and such specific codes as Hamming codes, the simplex codes, and many others.

A First Course in Coding Theory

A First Course in Coding Theory PDF Author: Raymond Hill
Publisher: Oxford University Press
ISBN: 9780198538035
Category : Computers
Languages : en
Pages : 268

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Book Description
Algebraic coding theory is a new and rapidly developing subject, popular for its many practical applications and for its fascinatingly rich mathematical structure. This book provides an elementary yet rigorous introduction to the theory of error-correcting codes. Based on courses given by the author over several years to advanced undergraduates and first-year graduated students, this guide includes a large number of exercises, all with solutions, making the book highly suitable for individual study.

Information Theory, Inference and Learning Algorithms

Information Theory, Inference and Learning Algorithms PDF Author: David J. C. MacKay
Publisher: Cambridge University Press
ISBN: 9780521642989
Category : Computers
Languages : en
Pages : 694

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Book Description
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.

Network Information Theory

Network Information Theory PDF Author: Abbas El Gamal
Publisher: Cambridge University Press
ISBN: 1139503146
Category : Technology & Engineering
Languages : en
Pages : 666

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Book Description
This comprehensive treatment of network information theory and its applications provides the first unified coverage of both classical and recent results. With an approach that balances the introduction of new models and new coding techniques, readers are guided through Shannon's point-to-point information theory, single-hop networks, multihop networks, and extensions to distributed computing, secrecy, wireless communication, and networking. Elementary mathematical tools and techniques are used throughout, requiring only basic knowledge of probability, whilst unified proofs of coding theorems are based on a few simple lemmas, making the text accessible to newcomers. Key topics covered include successive cancellation and superposition coding, MIMO wireless communication, network coding, and cooperative relaying. Also covered are feedback and interactive communication, capacity approximations and scaling laws, and asynchronous and random access channels. This book is ideal for use in the classroom, for self-study, and as a reference for researchers and engineers in industry and academia.

Elements of Information Theory

Elements of Information Theory PDF Author: Thomas M. Cover
Publisher: John Wiley & Sons
ISBN: 1118585771
Category : Computers
Languages : en
Pages : 788

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Book Description
The latest edition of this classic is updated with new problem sets and material The Second Edition of this fundamental textbook maintains the book's tradition of clear, thought-provoking instruction. Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory. All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide readers with a solid understanding of the underlying theory and applications. Problem sets and a telegraphic summary at the end of each chapter further assist readers. The historical notes that follow each chapter recap the main points. The Second Edition features: * Chapters reorganized to improve teaching * 200 new problems * New material on source coding, portfolio theory, and feedback capacity * Updated references Now current and enhanced, the Second Edition of Elements of Information Theory remains the ideal textbook for upper-level undergraduate and graduate courses in electrical engineering, statistics, and telecommunications.

Entropy and Information Theory

Entropy and Information Theory PDF Author: Robert M. Gray
Publisher: Springer Science & Business Media
ISBN: 1475739826
Category : Computers
Languages : en
Pages : 346

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Book Description
This book is devoted to the theory of probabilistic information measures and their application to coding theorems for information sources and noisy channels. The eventual goal is a general development of Shannon's mathematical theory of communication, but much of the space is devoted to the tools and methods required to prove the Shannon coding theorems. These tools form an area common to ergodic theory and information theory and comprise several quantitative notions of the information in random variables, random processes, and dynamical systems. Examples are entropy, mutual information, conditional entropy, conditional information, and discrimination or relative entropy, along with the limiting normalized versions of these quantities such as entropy rate and information rate. Much of the book is concerned with their properties, especially the long term asymptotic behavior of sample information and expected information. This is the only up-to-date treatment of traditional information theory emphasizing ergodic theory.