Presentation 1995/7/15
A study of data compaction by Bayes Coding
Atsushi Shimizu, Toshiyasu Matsushima, Shigeichi Hirasawa,
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Abstract(in English) Among the universal coding problems, Bayes Coding is one of the most active subject in the research field of recent data compaction. The Bayes Coding Algorithms for FSMX sources proposed in the recent researches use a fixed-depth context tree. In this paper, we study the compression ratio of the newly proposed algorithm which uses a variable-depth context tree, and investigate the difference of redundancy caused by prior probability distribution of prameters.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Bayes Coding / FSMX sources / context tree
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Committee IT
Conference Date 1995/7/15(1days)
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Registration To Information Theory (IT)
Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) A study of data compaction by Bayes Coding
Sub Title (in English)
Keyword(1) Bayes Coding
Keyword(2) FSMX sources
Keyword(3) context tree
1st Author's Name Atsushi Shimizu
1st Author's Affiliation Department of Industrial Engineering and Management School of Science and Engineering Waseda University()
2nd Author's Name Toshiyasu Matsushima
2nd Author's Affiliation Department of Industrial Engineering and Management School of Science and Engineering Waseda University
3rd Author's Name Shigeichi Hirasawa
3rd Author's Affiliation Department of Industrial Engineering and Management School of Science and Engineering Waseda University
Date 1995/7/15
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Volume (vol) vol.95
Number (no) 145
Page pp.pp.-
#Pages 6
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