Statistical Mechanics of Linear Compression Codes in Network Communication
Disordered Systems and Neural Networks
2007-05-23 v1 Statistical Mechanics
Abstract
We analyze the performance of a linear code used for a data compression of Slepian-Wolf type. In our framework, two correlated data are separately compressed into codewords employing Gallager-type codes and casted into a communication network through two independent input terminals. At the output terminal, the received codewords are jointly decoded by a practical algorithm based on the Thouless-Anderson-Palmer approach. Our analysis shows that the achievable rate region presented in the data compression theorem by Slepian and Wolf is described as first-order phase transitions among several phases. The typical performance of the practical decoder is also well evaluated by the replica method.
Cite
@article{arxiv.cond-mat/0106209,
title = {Statistical Mechanics of Linear Compression Codes in Network Communication},
author = {Tatsuto Murayama},
journal= {arXiv preprint arXiv:cond-mat/0106209},
year = {2007}
}
Comments
8 pages, 3 figures