A Class of Shannon-Mcmillan Approximation Theorems for Arbitrary Discrete Information Source
Received:April 11, 2005  Revised:August 15, 2006
Key Words: Shannon-Mcmillan theorem   arbitrary information source   small-deviation theorems   relative entropy density   $m$-order Markov information source.  
Fund Project:the National Natural Science Foundation of China (10571076); the Jiangsu Provicial Educaiton Department Natural Science Foundation (02KJD110003).
Author NameAffiliation
WANG Kang-kang School of Mathematics and Physics, Jiangsu University of Science and Technology, Zhenjiang 212003, China 
YANG Wei-guo Faculty of Science, Jiangsu University, Zhenjiang 212013, China 
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Abstract:
      In this paper, a class of small-deviation theorems for the relative entropy densities of the arbitrary stochastic sequence are discussed by comparing two joint distributions. As corollaries, some Shannon-Mcmillan theorems for arbitrary information source, $m$-order Markov information source are obtained and some results for the discrete information source are extended.
Citation:
DOI:10.3770/j.issn:1000-341X.2007.04.011
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