Bayes coding algorithm for FSM sources

Toshiyasu Matsushima, Shigeichi Hirasawa

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

    5 Citations (Scopus)

    Abstract

    The optimal universal code for FSMX sources (Rissanen, 1981) with respect to Bayes redundancy criterion (Davison, 1973) is deduced under the condition that the model, the probabilistic parameters, and the initial state are unknown. The algorithm is not only Bayes optimal for FSMX sources but also asymptotically optimal for a stationary ergodic sources. Further, the algorithm is regarded as a generalization of the Ziv-Lempel algorithm. In the basic CTW algorithm, the algorithm needs an initial context, where a finite constant is the depth of the context tree, for calculating the coding probability. For the problems of the initial situation and the infinite depth tree, the extensions to the CTW algorithm have been proposed in a paper by Willems (1994). In this paper, an optimal algorithm is proposed that gives solution against these problems from new point of view. This proposed method is also regarded as a generalization of the Ziv-Lempel algorithm.

    Original languageEnglish
    Title of host publicationIEEE International Symposium on Information Theory - Proceedings
    Place of PublicationPiscataway, NJ, United States
    PublisherIEEE
    Pages388
    Number of pages1
    Publication statusPublished - 1995
    EventProceedings of the 1995 IEEE International Symposium on Information Theory - Whistler, BC, Can
    Duration: 1995 Sep 171995 Sep 22

    Other

    OtherProceedings of the 1995 IEEE International Symposium on Information Theory
    CityWhistler, BC, Can
    Period95/9/1795/9/22

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    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Applied Mathematics
    • Modelling and Simulation
    • Theoretical Computer Science
    • Information Systems

    Cite this

    Matsushima, T., & Hirasawa, S. (1995). Bayes coding algorithm for FSM sources. In IEEE International Symposium on Information Theory - Proceedings (pp. 388). IEEE.