Reducing the space complexity of a bayes coding algorithm using an expanded context tree

Toshiyasu Matsushima, Shigeich Hirasawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

The context tree models are widely used in a lot of research fields. Patricia[7] like trees are applied to the context trees that are expanded according to the increase of the length of a source sequence in the previous researches of non-predictive source coding and model selection. The space complexity of the Patricia like context trees are O(t) where t is the length of a source sequence. On the other hand, the predictive Bayes source coding algorithm cannot use a Patricia like context tree, because it is difficult to hold and update the posterior probability parameters on a Patricia like tree. So the space complexity of the expanded trees in the predictive Bayes coding algorithm is O(t2). In this paper, we propose an efficient predictive Bayes coding algorithm using a new representation of the posterior probability parameters and the compact context tree holding the parameters whose space complexity is O(t).

Original languageEnglish
Title of host publication2009 IEEE International Symposium on Information Theory, ISIT 2009
Pages719-723
Number of pages5
DOIs
Publication statusPublished - 2009 Nov 19
Event2009 IEEE International Symposium on Information Theory, ISIT 2009 - Seoul, Korea, Republic of
Duration: 2009 Jun 282009 Jul 3

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8102

Conference

Conference2009 IEEE International Symposium on Information Theory, ISIT 2009
CountryKorea, Republic of
CitySeoul
Period09/6/2809/7/3

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modelling and Simulation
  • Applied Mathematics

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    Matsushima, T., & Hirasawa, S. (2009). Reducing the space complexity of a bayes coding algorithm using an expanded context tree. In 2009 IEEE International Symposium on Information Theory, ISIT 2009 (pp. 719-723). [5205677] (IEEE International Symposium on Information Theory - Proceedings). https://doi.org/10.1109/ISIT.2009.5205677