Bayes universal coding algorithm for side information context tree models

Toshiyasu Matsushima, Shigeich Hirasawa

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

    Abstract

    The problem of universal codes with side information is investigated from Bayes criterion. We propose side information context tree models which are an extension of context tree models to sources with side information. Assuming a special class of the prior distributions for side information context tree models, we propose an efficient algorithm of Bayes code for the models. The asymptotic code length of the Bayes codes with side information is also investigated.

    Original languageEnglish
    Title of host publicationIEEE International Symposium on Information Theory - Proceedings
    Pages2345-2348
    Number of pages4
    Volume2005
    DOIs
    Publication statusPublished - 2005
    Event2005 IEEE International Symposium on Information Theory, ISIT 05 - Adelaide
    Duration: 2005 Sep 42005 Sep 9

    Other

    Other2005 IEEE International Symposium on Information Theory, ISIT 05
    CityAdelaide
    Period05/9/405/9/9

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering

    Cite this

    Matsushima, T., & Hirasawa, S. (2005). Bayes universal coding algorithm for side information context tree models. In IEEE International Symposium on Information Theory - Proceedings (Vol. 2005, pp. 2345-2348). [1523767] https://doi.org/10.1109/ISIT.2005.1523767