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Author: Jerry Gibson Publisher: Morgan & Claypool Publishers ISBN: 1598298089 Category : Technology & Engineering Languages : en Pages : 129
Book Description
This book is very specifically targeted to problems in communications and compression by providing the fundamental principles and results in information theory and rate distortion theory for these applications and presenting methods that have proved and will prove useful in analyzing and designing real systems. The chapters contain treatments of entropy, mutual information, lossless source coding, channel capacity, and rate distortion theory; however, it is the selection, ordering, and presentation of the topics within these broad categories that is unique to this concise book. While the coverage of some standard topics is shortened or eliminated, the standard, but important, topics of the chain rules for entropy and mutual information, relative entropy, the data processing inequality, and the Markov chain condition receive a full treatment. Similarly, lossless source coding techniques presented include the Lempel-Ziv-Welch coding method. The material on rate Distortion theory and exploring fundamental limits on lossy source coding covers the often-neglected Shannon lower bound and the Shannon backward channel condition, rate distortion theory for sources with memory, and the extremely practical topic of rate distortion functions for composite sources. The target audience for the book consists of graduate students at the master's degree level and practicing engineers. It is hoped that practicing engineers can work through this book and comprehend the key results needed to understand the utility of information theory and rate distortion theory and then utilize the results presented to analyze and perhaps improve the communications and compression systems with which they are familiar.
Author: Jerry Gibson Publisher: Morgan & Claypool Publishers ISBN: 1598298089 Category : Technology & Engineering Languages : en Pages : 129
Book Description
This book is very specifically targeted to problems in communications and compression by providing the fundamental principles and results in information theory and rate distortion theory for these applications and presenting methods that have proved and will prove useful in analyzing and designing real systems. The chapters contain treatments of entropy, mutual information, lossless source coding, channel capacity, and rate distortion theory; however, it is the selection, ordering, and presentation of the topics within these broad categories that is unique to this concise book. While the coverage of some standard topics is shortened or eliminated, the standard, but important, topics of the chain rules for entropy and mutual information, relative entropy, the data processing inequality, and the Markov chain condition receive a full treatment. Similarly, lossless source coding techniques presented include the Lempel-Ziv-Welch coding method. The material on rate Distortion theory and exploring fundamental limits on lossy source coding covers the often-neglected Shannon lower bound and the Shannon backward channel condition, rate distortion theory for sources with memory, and the extremely practical topic of rate distortion functions for composite sources. The target audience for the book consists of graduate students at the master's degree level and practicing engineers. It is hoped that practicing engineers can work through this book and comprehend the key results needed to understand the utility of information theory and rate distortion theory and then utilize the results presented to analyze and perhaps improve the communications and compression systems with which they are familiar.
Author: Jerry Gibson Publisher: Springer Nature ISBN: 3031016807 Category : Technology & Engineering Languages : en Pages : 115
Book Description
This book is very specifically targeted to problems in communications and compression by providing the fundamental principles and results in information theory and rate distortion theory for these applications and presenting methods that have proved and will prove useful in analyzing and designing real systems. The chapters contain treatments of entropy, mutual information, lossless source coding, channel capacity, and rate distortion theory; however, it is the selection, ordering, and presentation of the topics within these broad categories that is unique to this concise book. While the coverage of some standard topics is shortened or eliminated, the standard, but important, topics of the chain rules for entropy and mutual information, relative entropy, the data processing inequality, and the Markov chain condition receive a full treatment. Similarly, lossless source coding techniques presented include the Lempel-Ziv-Welch coding method. The material on rate Distortion theory and exploring fundamental limits on lossy source coding covers the often-neglected Shannon lower bound and the Shannon backward channel condition, rate distortion theory for sources with memory, and the extremely practical topic of rate distortion functions for composite sources.
Author: Jerry D. Gibson Publisher: ISBN: 9781601987792 Category : Data compression Languages : en Pages : 136
Book Description
Numerous voice, still image, audio, and video compression standards have been developed over the last 25 years, and significant advances in the state of the art have been achieved. However, in the more than 50 years since Shannon's seminal 1959 paper, no rate distortion bounds for voice and video have been forthcoming. In this volume, we present the first rate distortion bounds for voice and video that actually lower bound the operational rate distortion performance of the best-performing voice and video codecs. The bounds indicate that improvements in rate distortion performance of approximately 50% over the best-performing voice and video codecs are possible. Research directions to improve the new bounds are discussed.
Author: Stefan Host Publisher: John Wiley & Sons ISBN: 1119433789 Category : Technology & Engineering Languages : en Pages : 373
Book Description
An important text that offers an in-depth guide to how information theory sets the boundaries for data communication In an accessible and practical style, Information and Communication Theory explores the topic of information theory and includes concrete tools that are appropriate for real-life communication systems. The text investigates the connection between theoretical and practical applications through a wide-variety of topics including an introduction to the basics of probability theory, information, (lossless) source coding, typical sequences as a central concept, channel coding, continuous random variables, Gaussian channels, discrete input continuous channels, and a brief look at rate distortion theory. The author explains the fundamental theory together with typical compression algorithms and how they are used in reality. He moves on to review source coding and how much a source can be compressed, and also explains algorithms such as the LZ family with applications to e.g. zip or png. In addition to exploring the channel coding theorem, the book includes illustrative examples of codes. This comprehensive text: Provides an adaptive version of Huffman coding that estimates source distribution Contains a series of problems that enhance an understanding of information presented in the text Covers a variety of topics including optimal source coding, channel coding, modulation and much more Includes appendices that explore probability distributions and the sampling theorem Written for graduate and undergraduate students studying information theory, as well as professional engineers, master’s students, Information and Communication Theory offers an introduction to how information theory sets the boundaries for data communication.
Author: Raymond W. Yeung Publisher: Springer Science & Business Media ISBN: 9780306467912 Category : Computers Languages : en Pages : 440
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.
Author: Thomas M. Cover Publisher: Wiley-Interscience ISBN: Category : Computers Languages : en Pages : 576
Book Description
Following a brief introduction and overview, early chapters cover the basic algebraic relationships of entropy, relative entropy and mutual information, AEP, entropy rates of stochastics processes and data compression, duality of data compression and the growth rate of wealth. Later chapters explore Kolmogorov complexity, channel capacity, differential entropy, the capacity of the fundamental Gaussian channel, the relationship between information theory and statistics, rate distortion and network information theories. The final two chapters examine the stock market and inequalities in information theory. In many cases the authors actually describe the properties of the solutions before the presented problems.
Author: Jerry D. Gibson Publisher: Springer ISBN: 9783031653872 Category : Technology & Engineering Languages : en Pages : 0
Book Description
This book provides readers with the fundamentals of information theoretic techniques for statistical data science analyses and for characterizing the behavior and performance of a learning agent outside of the standard results on communications and compression fundamental limits. Readers will benefit from the presentation of information theoretic quantities, definitions, and results that provide or could provide insights into data science and learning.
Author: Fady Alajaji Publisher: Springer ISBN: 9811080011 Category : Mathematics Languages : en Pages : 333
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: Jerry Gibson
Author: Jerry Gibson
Author: Jerry Gibson
Author: Jerry D. Gibson
Author: Stefan Host
Author: Sergio Verdú
Author: Raymond W. Yeung
Author: Thomas M. Cover
Author: Toby Berger
Author: Jerry D. Gibson
Author: Fady Alajaji