From the Inside Flap:
Elements of Information Theory is an up-to-date introduction to the field of information theory and its applications to communication theory, statistics, computer science, probability theory, and the theory of investment. Covering all the essential topics in information theory, this comprehensive work provides an accessible introduction to the field that blends theory and applications. In step-by-step detail, the authors introduce the basic quantities of entropy, relative entropy, and mutual information and show how they arise as natural answers to questions of data compression, channel capacity, rate distortion, hypothesis testing, information flow in networks, and gambling. In addition, Elements of Information Theory investigates a number of ideas never before covered at this level in a textbook, including:
* The relationship of the second law of thermodynamics to Markov chains
* Competitive optimality of Huffman codes
* The duality of data compression and gambling
* Lempel Ziv coding
* Kolmogorov complexity
* Portfolio theory
* Inequalities in information theory and their consequences in mathematics
Complete with numerous illustrations, original problems and historical notes, Elements of Information Theory is a practical reference for communications professionals and statisticians specializing in information theory. It also serves as an excellent introductory text for senior and graduate students taking courses in telecommunications, electrical engineering, statistics, computer science, and economics.
About the Author:
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 1984-85 and the IBM Graduate Fellowship for 1987-90. 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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