Structural Information in Two-Dimensional Patterns: Entropy Convergence and Excess Entropy
统计力学
2009-11-07 v1
摘要
We develop information-theoretic measures of spatial structure and pattern in more than one dimension. As is well known, the entropy density of a two-dimensional configuration can be efficiently and accurately estimated via a converging sequence of conditional entropies. We show that the manner in which these conditional entropies converge to their asymptotic value serves as a measure of global correlation and structure for spatial systems in any dimension. We compare and contrast entropy-convergence with mutual-information and structure-factor techniques for quantifying and detecting spatial structure.
引用
@article{arxiv.cond-mat/0212078,
title = {Structural Information in Two-Dimensional Patterns: Entropy Convergence and Excess Entropy},
author = {David P. Feldman and James P. Crutchfield},
journal= {arXiv preprint arXiv:cond-mat/0212078},
year = {2009}
}
备注
11 pages, 5 figures, http://www.santafe.edu/projects/CompMech/papers/2dnnn.html