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Elements of Information Theory
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See moreThe 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.
Book Hero Magic formatted this description to make it easier to read. While it's new and
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Description
Elements of Information Theory, Second Edition, covers the standard topics of information theory, such as entropy, data compression, channel capacity, rate distortion, multi-user theory, and hypothesis testing. It presents applications to communications, statistics, complexity theory, and investment.
Chapters 1-9 cover the asymptotic equipartition property, data compression, and channel capacity, culminating in the capacity of the Gaussian channel. Chapters 10-17 include rate distortion, the method of types, Kolmogorov complexity, network information theory, universal source coding, and portfolio theory.
The first edition of this book is the most successful book on information theory on the market today. Adoptions have remained strong since the book's publication in 1991.
Book Hero Magic summarised reviews for this book. While it's new and still learning, it may not be perfect - your feedback is welcome! HOW HAS THIS BEEN REVIEWED?
Elements of Information Theory is praised for its exceptional exposition quality, providing clear explanations, useful graphical illustrations, and insightful mathematical derivations, which make it highly valuable as a textbook. It is also recommended as a comprehensive reference in the field of information theory.
Book Details
INFORMATION
ISBN: 9780471241959
Publisher: John Wiley & Sons Inc
Format: Hardback
Date Published: 08 September 2006
Country: United States
Imprint: Wiley-Interscience
Edition: 2nd edition
Audience: Tertiary education
DIMENSIONS
Spine width: 41.0mm
Width: 163.0mm
Height: 241.0mm
Weight: 1157g
Pages: 784
About the Author
THOMAS M. COVER, PHD, is Professor in the departments of electrical engineering and statistics, Stanford University. A recipient of the 1991 IEEE Claude E. Shannon Award, Dr. Cover is a past president of the IEEE Information Theory Society, a Fellow of the IEEE and the Institute of Mathematical Statistics, and a member of the National Academy of Engineering and the American Academy of Arts and Science. He has authored more than 100 technical papers and 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 organizing unstructured information. After receiving his PhD at Stanford, Dr. Thomas spent more than nine years at the IBM T. J. Watson Research Center in Yorktown Heights, New York. Dr. Thomas is a recipient of the IEEE Charles LeGeyt Fortescue Fellowship.
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