Summary
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.
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Table of Contents
1. Introduction and Preview.
2. Entropy, Relative Entropy and Mutual Information.
3. The Asymptotic Equipartition Property.
4. Entropy oRates of a Stochastic Process.
5. Data Compression.
6. Gambling and Data Compression.
7. Channel Capacity.
8. Differential Entropy.
9. The Gaussian Channel.
10. Rate Distortion Theory.
11. Information Theory and Statistics.
12. Maximum Entropy.
13. Universal Source Coding.
14. Kolmogorov Complexity.
15. Network Information Theory.
16. Information Theory and Portfolio Theory.
17. Inequalities in Information Theory.
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