Bayes coding algorithm using context tree

Toshiyasu Matsushima*, Shigeichi Hirasawa

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

8 Citations (Scopus)


The context tree weighting (CTW) algorithm has high compressibility for the universal coding with respect to FSMX sources. In this paper, we propose an algorithm by reinterpreting the CTW algorithm from the viewpoint of Bayes coding. Our 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 previously studied. Moreover, the proposed algorithm is free from underflow which frequently occurs in the CTW procedure.

Original languageEnglish
Publication statusPublished - 1994 Dec 1
EventProceedings of the 1994 IEEE International Symposium on Information Theory - Trodheim, Norw
Duration: 1994 Jun 271994 Jul 1


OtherProceedings of the 1994 IEEE International Symposium on Information Theory
CityTrodheim, Norw

ASJC Scopus subject areas

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


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