Elements of information theory

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Wiley, Aug 26, 1991 - Computers - 542 pages
5 Reviews
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.

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Review: Elements of Information Theory

User Review  - Jason Yang - Goodreads

Cover and Thomas is THE classic information theory textbook. Here, the authors took on the ambitious task of making a comprehensive survey of (the still evolving) information theory. Admittedly, I got ... Read full review

Review: Elements of Information Theory

User Review  - Huyen - Goodreads

Pure gold. A classic in Information Theory. Read full review

Contents

List of Figures
1
Entropy Relative Entropy and Mutual Information
12
The Asymptotic Equipartition Property
50
Copyright

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About the author (1991)

About the authors THOMAS M. COVER is Professor jointly in the Departments of Electrical Engineering and Statistics at Stanford University. He is past President of the IEEE Information Theory Society and is a Fellow of the Institute for Mathematical Statistics and of the IEEE. In 1972 he received the Outstanding Paper Award in information Theory for his paper "Broadcast Channels," and he was selected in 1990 as the Shannon Lecturer, regarded as the highest honor in information theory. Author of over 90 technical papers, he is coeditor of the book Open Problems in Communication and Computation. Professor Cover has devoted the last 20 years to developing the relationship between information theory and statistics. He received his PhD in electrical engineering from Stanford University. JOY A. THOMAS is working at the IBM T. J. Watson Research Center in Hawthorne, New York. He received the IEEE Charles LeGeyt Fortescue Fellowship for 198485 and the IBM Graduate Fellowship for 198790. He received his BTech in electrical engineering at the Indian Institute of Technology Madras, India and his PhD in electrical engineering at Stanford University.

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