Information theory for continuous systems
This book provides a systematic mathematical analysis of entropy and stochastic processes, especially Gaussian processes, and its applications to information theory. The contents fall roughly into two parts. In the first part a unified treatment of entropy in information theory, probability theory and mathematical statistics is presented. The second part deals mostly with information theory for continuous communication systems. Particular emphasis is placed on the Gaussian channel. An advantage…
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- Full title :Information theory for continuous systems / Shunsuke Ihara.
Summary
This book provides a systematic mathematical analysis of entropy and stochastic processes, especially Gaussian processes, and its applications to information theory. The contents fall roughly into two parts. In the first part a unified treatment of entropy in information theory, probability theory and mathematical statistics is presented. The second part deals mostly with information theory for continuous communication systems. Particular emphasis is placed on the Gaussian channel. An advantage of this book is that, unlike most books on information theory, it places emphasis on continuous communication systems, rather than discrete ones.
Read More ↓Edition Statements
- Publication Date:©1993.
Publication Statements
- Publisher(s):World Scientific
- Place of Publication:Singapore
- Language:eng
- Publication Date:©1993.
The Physical Object
- Description:1 online resource (xiii, 308 pages) : : illustrations
Edition Identifiers
- ISBN:9789814355827, 9814355828
- oclc:ocn844939540
- LC Classification:Q370
- Dewey Decimal:003/.54
Table of Contents
Ch. 1. Entropy. 1.1. Information transmission -- 1.2. Entropy -- 1.3. Entropy for continuous distributions -- 1.4. Relative entropy -- 1.5. Properties of relative entropy -- 1.6. Mutual information -- 1.7. Rate-distortion function -- 1.8. Entropy for Gaussian distributions -- Historical notes -- ch. 2. Stochastic processes and entropy. 2.1. Entropy rate -- 2.2. Discrete time stationary processes -- 2.3. Discrete time Markov stationary processes -- 2.4. Entropy rate of a stationary Gaussian process -- 2.5. Continuous time stationary processes -- 2.6. Band limited processes -- 2.7. Discrete time observation of continuous time processes -- Historical notes -- ch. 3. Maximum entropy analysis. 3.1. Maximum entropy and minimum relative entropy -- 3.2. Large deviation theorems -- 3.3. Maximum entropy spectral analysis -- 3.4. Hypothesis testing -- 3.5. Hypothesis testing for stationary Gaussian processes -- Historical notes -- ch. 4. Theory of information transmission. 4.1. Model of communication systems -- 4.2. Information stability -- 4.3. Source coding theorems -- 4.4. Channel capacity -- 4.5. Channel coding theorems -- 4.6. Fundamental theorem in information transmission -- Historica…
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