Elements of Information Theory

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John Wiley & Sons, Nov 28, 2012 - Computers - 776 pages
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The latest edition of this classic is updated with new problem setsand material

The Second Edition of this fundamental textbook maintains thebook's tradition of clear, thought-provoking instruction. Readersare provided once again with an instructive mix of mathematics,physics, statistics, and information theory.

All the essential topics in information theory are covered indetail, including entropy, data compression, channel capacity, ratedistortion, network information theory, and hypothesis testing. Theauthors provide readers with a solid understanding of theunderlying theory and applications. Problem sets and a telegraphicsummary at the end of each chapter further assist readers. Thehistorical notes that follow each chapter recap the mainpoints.

The Second Edition features:
* Chapters reorganized to improve teaching
* 200 new problems
* New material on source coding, portfolio theory, and feedbackcapacity
* Updated references

Now current and enhanced, the Second Edition of Elements ofInformation Theory remains the ideal textbook for upper-levelundergraduate and graduate courses in electrical engineering,statistics, and telecommunications.

An Instructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment.

 

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excellent

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This is a good book in general, but there are many places in this books that are not so self-explanatory. The authors do not explain. They probably think it is very obvious, but it might seems as obvious to the readers even with backgrounds.

Contents

Entropy Relative Entropy and Mutual
Asymptotic Equipartition Property
Entropy Rates of a Stochastic Process
Data Compression
Gambling and Data Compression
Channel Capacity
Maximum Entropy
Differential Entropy
Information Theory and Statistics
Universal Source Coding
Kolmogorov Complexity
Network Information Theory
Information Theory and Portfolio Theory
Inequalities in Information Theoq
Bibliography
List of Symbols

Gaussian Channel
Rate Distortion Theoq
Index
Copyright

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About the author (2012)

THOMAS M. COVER, PHD, is Professor in the departments ofelectrical engineering and statistics, Stanford University. Arecipient of the 1991 IEEE Claude E. Shannon Award, Dr. Cover is apast president of the IEEE Information Theory Society, a Fellow ofthe IEEE and the Institute of Mathematical Statistics, and a memberof the National Academy of Engineering and the American Academy ofArts and Science. He has authored more than 100 technical papersand is coeditor of Open Problems in Communication and Computation.

JOY A. THOMAS, PHD, is the Chief Scientist at Stratify,Inc., a Silicon Valley start-up specializing in organizingunstructured information. After receiving his PhD at Stanford, Dr.Thomas spent more than nine years at the IBM T. J. Watson ResearchCenter in Yorktown Heights, New York. Dr. Thomas is a recipient ofthe IEEE Charles LeGeyt Fortescue Fellowship.

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