Bayes coding algorithm using context tree

Toshiyasu Matsushima, Shigeichi Hirasawa

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

    1 Citation (Scopus)

    Abstract

    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
    Title of host publicationIEEE International Symposium on Information Theory - Proceedings
    Place of PublicationPiscataway, NJ, United States
    PublisherIEEE
    Publication statusPublished - 1994
    EventProceedings of the 1994 IEEE International Symposium on Information Theory - Trodheim, Norw
    Duration: 1994 Jun 271994 Jul 1

    Other

    OtherProceedings of the 1994 IEEE International Symposium on Information Theory
    CityTrodheim, Norw
    Period94/6/2794/7/1

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    ASJC Scopus subject areas

    • Electrical and Electronic Engineering

    Cite this

    Matsushima, T., & Hirasawa, S. (1994). Bayes coding algorithm using context tree. In IEEE International Symposium on Information Theory - Proceedings IEEE.