Entropy and information theory
著者
書誌事項
Entropy and information theory
Springer-Verlag, c1990
- : gw
- : us
大学図書館所蔵 件 / 全66件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Bibliography: p. 315-326
Includes index
内容説明・目次
- 巻冊次
-
: us ISBN 9780387973715
内容説明
This book is devoted to the theory of probabilistic information measures and their application to coding theorems for information sources and noisy channels. 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, especially the long term asymptotic behavior of sample information and expected information. This is the only up-to-date treatment of traditional information theory emphasizing ergodic theory.
- 巻冊次
-
: gw ISBN 9783540973713
内容説明
This text is devoted to the theory of probabilistic information measures and their application to coding theorems for information sources and noisy channels. 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 compromise several quantitative notions of the information in random variables, random processes and dynamical systems. Examples are entropy, mutual 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, especially the long term asymptotic behaviour of sample information and expected information.
目次
Contents: Information Sources.- Entropy and Information.- The Entropy Ergodic Theorem.- Information Rates I.- Relative Entropy.- Information Rates II.- Relative Entropy Rates.- Ergodic Theorems for Densities.- Channels and Codes.- Distortion.- Source Coding Theorems.- Coding for Noisy Channels.- Bibliography.- Index.
「Nielsen BookData」 より