information theory

dextrad

【文件名】:0694@52RD_information_theory.part1.rar
【格　式】:rar
【大　小】:900K
【简　介】:This book is devoted to the theory of probabilistic information measures and their application to coding theorems for information sources and noisy chan-nels. The eventual goal is a general development of Shannon's mathematical theory of communication, but much of the space is devoted to the tools and methods required to prove the Shannon coding theorems. These tools form an area common to ergodic theory and information theory and comprise several quantitative notions of the information in random variables, random processes,and dynamical systems. Examples are entropy, mutual information, conditional entropy, conditional information, and discrimination or relative entropy, along with the limiting normalized versions of these quantities such as entropy rate and information rate. Much of the book is concerned with their properties, es-pecially the long term asymptotic behavior of sample information and expected information.
【目　录】:
1 Information Sources
2 Entropy and Information
3 The Entropy Ergodic Theorem
4 Information Rates I
5 Relative Entropy
6 Information Rates II
7 Relative Entropy Rates
8 Ergodic Theorems for Densities
9 Channels and Codes
10 Distortion
11 Source Coding Theorems
12 Coding for noisy channels
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dextrad

【文件名】:0694@52RD_information_theory.part2.rar
【格　式】:rar
【大　小】:283K
【简　介】:
【目　录】:

liaoliao

thanks very much!
[em05]