文件名称：Entropy And Information Theory - Robert M Gray - Springer-Verlag
文件大小：1.42MB
文件格式：PDF
更新时间：2014-05-30 10:20:32
maths entropy information
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.