Reducing the space complexity of a bayes coding algorithm using an expanded context tree

Toshiyasu Matsushima, Shigeich Hirasawa

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

    3 Citations (Scopus)

    Abstract

    The context tree models are widely used in a lot of research fields. Patricia[7] like trees are applied to the context trees that are expanded according to the increase of the length of a source sequence in the previous researches of non-predictive source coding and model selection. The space complexity of the Patricia like context trees are O(t) where t is the length of a source sequence. On the other hand, the predictive Bayes source coding algorithm cannot use a Patricia like context tree, because it is difficult to hold and update the posterior probability parameters on a Patricia like tree. So the space complexity of the expanded trees in the predictive Bayes coding algorithm is O(t2). In this paper, we propose an efficient predictive Bayes coding algorithm using a new representation of the posterior probability parameters and the compact context tree holding the parameters whose space complexity is O(t).

    Original languageEnglish
    Title of host publicationIEEE International Symposium on Information Theory - Proceedings
    Pages719-723
    Number of pages5
    DOIs
    Publication statusPublished - 2009
    Event2009 IEEE International Symposium on Information Theory, ISIT 2009 - Seoul
    Duration: 2009 Jun 282009 Jul 3

    Other

    Other2009 IEEE International Symposium on Information Theory, ISIT 2009
    CitySeoul
    Period09/6/2809/7/3

    Fingerprint

    Space Complexity
    Bayes
    Coding
    Source Coding
    Posterior Probability
    Context
    Model Selection
    Parameter Space
    Update

    ASJC Scopus subject areas

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

    Cite this

    Matsushima, T., & Hirasawa, S. (2009). Reducing the space complexity of a bayes coding algorithm using an expanded context tree. In IEEE International Symposium on Information Theory - Proceedings (pp. 719-723). [5205677] https://doi.org/10.1109/ISIT.2009.5205677

    Reducing the space complexity of a bayes coding algorithm using an expanded context tree. / Matsushima, Toshiyasu; Hirasawa, Shigeich.

    IEEE International Symposium on Information Theory - Proceedings. 2009. p. 719-723 5205677.

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

    Matsushima, T & Hirasawa, S 2009, Reducing the space complexity of a bayes coding algorithm using an expanded context tree. in IEEE International Symposium on Information Theory - Proceedings., 5205677, pp. 719-723, 2009 IEEE International Symposium on Information Theory, ISIT 2009, Seoul, 09/6/28. https://doi.org/10.1109/ISIT.2009.5205677
    Matsushima T, Hirasawa S. Reducing the space complexity of a bayes coding algorithm using an expanded context tree. In IEEE International Symposium on Information Theory - Proceedings. 2009. p. 719-723. 5205677 https://doi.org/10.1109/ISIT.2009.5205677
    Matsushima, Toshiyasu ; Hirasawa, Shigeich. / Reducing the space complexity of a bayes coding algorithm using an expanded context tree. IEEE International Symposium on Information Theory - Proceedings. 2009. pp. 719-723
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