Bayes universal coding algorithm for side information context tree models

Toshiyasu Matsushima; Shigeich Hirasawa

doi:10.1109/ISIT.2005.1523767

Bayes universal coding algorithm for side information context tree models

Toshiyasu Matsushima^*, Shigeich Hirasawa

^*Corresponding author for this work

School of Fundamental Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Proceedings of the 2005 IEEE International Symposium on Information Theory, ISIT 05
Pages	2345-2348
Number of pages	4
DOIs	https://doi.org/10.1109/ISIT.2005.1523767
Publication status	Published - 2005 Dec 1
Event	2005 IEEE International Symposium on Information Theory, ISIT 05 - Adelaide, Australia Duration: 2005 Sept 4 → 2005 Sept 9

Publication series

Name	IEEE International Symposium on Information Theory - Proceedings
Volume	2005
ISSN (Print)	2157-8099

Conference

Conference	2005 IEEE International Symposium on Information Theory, ISIT 05
Country/Territory	Australia
City	Adelaide
Period	05/9/4 → 05/9/9

ASJC Scopus subject areas

Theoretical Computer Science
Information Systems
Modelling and Simulation
Applied Mathematics

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10.1109/ISIT.2005.1523767

Cite this

Bayes universal coding algorithm for side information context tree models. / Matsushima, Toshiyasu; Hirasawa, Shigeich.
Proceedings of the 2005 IEEE International Symposium on Information Theory, ISIT 05. 2005. p. 2345-2348 1523767 (IEEE International Symposium on Information Theory - Proceedings; Vol. 2005).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Matsushima, T & Hirasawa, S 2005, Bayes universal coding algorithm for side information context tree models. in Proceedings of the 2005 IEEE International Symposium on Information Theory, ISIT 05., 1523767, IEEE International Symposium on Information Theory - Proceedings, vol. 2005, pp. 2345-2348, 2005 IEEE International Symposium on Information Theory, ISIT 05, Adelaide, Australia, 05/9/4. https://doi.org/10.1109/ISIT.2005.1523767

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doi = "10.1109/ISIT.2005.1523767",

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AB - 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.

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Bayes universal coding algorithm for side information context tree models

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