The Dynamic Phase Transition for Decoding Algorithms
无序系统与神经网络
2016-08-31 v1 统计力学
摘要
The state-of-the-art error correcting codes are based on large random constructions (random graphs, random permutations, ...) and are decoded by linear-time iterative algorithms. Because of these features, they are remarkable examples of diluted mean-field spin glasses, both from the static and from the dynamic points of view. We analyze the behavior of decoding algorithms using the mapping onto statistical-physics models. This allows to understand the intrinsic (i.e. algorithm independent) features of this behavior.
引用
@article{arxiv.cond-mat/0205051,
title = {The Dynamic Phase Transition for Decoding Algorithms},
author = {Silvio Franz and Michele Leone and Andrea Montanari and Federico Ricci-Tersenghi},
journal= {arXiv preprint arXiv:cond-mat/0205051},
year = {2016}
}
备注
40 pages, 29 eps figures