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 publicationIEEE International Symposium on Information Theory - Proceedings
    Pages386
    Number of pages1
    DOIs
    Publication statusPublished - 1994
    Event1994 IEEE International Symposium on Information Theory, ISIT 1994 - Trondheim
    Duration: 1994 Jun 271994 Jul 1

    Other

    Other1994 IEEE International Symposium on Information Theory, ISIT 1994
    CityTrondheim
    Period94/6/2794/7/1

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    ASJC Scopus subject areas

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

    Cite this

    Matsushima, T., & Hirasawa, S. (1994). A Bayes coding algorithm using context tree. In IEEE International Symposium on Information Theory - Proceedings (pp. 386). [394633] https://doi.org/10.1109/ISIT.1994.394633