Entropy and Information Theory is popular PDF and ePub book, written by Robert M. Gray in 2013-03-14, it is a fantastic choice for those who relish reading online the Computers genre. Let's immerse ourselves in this engaging Computers book by exploring the summary and details provided below. Remember, Entropy and Information Theory can be Read Online from any device for your convenience.
Entropy and Information Theory Book PDF Summary
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.
Detail Book of Entropy and Information Theory PDF
- Author : Robert M. Gray
- Release : 14 March 2013
- Publisher : Springer Science & Business Media
- ISBN : 9781475739824
- Genre : Computers
- Total Page : 346 pages
- Language : English
- PDF File Size : 9,9 Mb
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