A Bayes coding algorithm using context tree

Toshiyasu Matsushima, Shigeichi Hirasawa

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

Abstract

The context tree weighting (CTW) algorithm [Willems et al., 1993] has high compressibility for universal coding with respect to FSMX sources. The present authors propose an algorithm by reinterpreting the CTW algorithm from the viewpoint of Bayes coding. This algorithm can be applied to a wide class of prior distribution for finite alphabet FSMX sources. The algorithm is regarded as both a generalized version of the CTW procedure and a practical algorithm using a context tree of the adaptive Bayes coding which has been studied in Mataushima et al. (1991). Moreover, the proposed algorithm is free from underflow which frequently occurs in the CTW procedure.

Original languageEnglish
Title of host publicationProceedings - 1994 IEEE International Symposium on Information Theory, ISIT 1994
Number of pages1
DOIs
Publication statusPublished - 1994 Dec 1
Event1994 IEEE International Symposium on Information Theory, ISIT 1994 - Trondheim, Norway
Duration: 1994 Jun 271994 Jul 1

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095

Conference

Conference1994 IEEE International Symposium on Information Theory, ISIT 1994
CountryNorway
CityTrondheim
Period94/6/2794/7/1

ASJC Scopus subject areas

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

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