An algorithm for universal lossless compression with side information

被引：19
|
作者：
Cai, Haixiao [1 ]
Kulkarni, Sanjeev R. [1 ]
Verdu, Sergio [1 ]
机构：
[1] Princeton Univ, Dept Elect Engn, Princeton, NJ 08544 USA
来源：
IEEE TRANSACTIONS ON INFORMATION THEORY | 2006年 / 52卷 / 09期
基金：
美国国家科学基金会;
关键词：
arithmetic coding; conditional entropy; context tree weighting method; hidden Markov process; source coding; universal lossless data compression;
D O I：
10.1109/TIT.2006.880020
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper proposes a new algorithm based on the Context-Tree Weighting (CTW) method for universal compression of a finite-alphabet sequence x(1)(n) with side information y(1)(n) available to both the encoder and decoder. We prove that with probability one the compression ratio converges to the conditional entropy rate for jointly stationary ergodic sources. Experimental results with Markov chains and English texts show the effectiveness of the algorithm.
引用
收藏
页码：4008 / 4016
页数：9
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