A Bayes coding algorithm using context tree

Author

Matsushima, Toshiyasu ; Hirasawa, Shigeichi

Author_Institution

Sch. of Sci. & Eng., Waseda Univ., Tokyo, Japan

fYear

1994

fDate

27 Jun-1 Jul 1994

Firstpage

386

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

Keywords

Bayes methods; adaptive codes; source coding; trees (mathematics); Bayes coding algorithm; CTW algorithm; FSMX sources; adaptive Bayes coding; compressibility; context tree weighting algorithm; finite alphabet FSMX sources; prior distribution; underflow; universal coding; Artificial intelligence;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on

Conference_Location

Trondheim

Print_ISBN

0-7803-2015-8

Type

conf

DOI

10.1109/ISIT.1994.394633

Filename

394633

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2617977