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关于广义图熵的信息不平等问题。

Towards information inequalities for generalized graph entropies.

作者信息

Sivakumar Lavanya, Dehmer Matthias

机构信息

Institute of Mathematical Sciences, Chennai, India.

出版信息

PLoS One. 2012;7(6):e38159. doi: 10.1371/journal.pone.0038159. Epub 2012 Jun 8.

Abstract

In this article, we discuss the problem of establishing relations between information measures for network structures. Two types of entropy based measures namely, the Shannon entropy and its generalization, the Rényi entropy have been considered for this study. Our main results involve establishing formal relationships, by means of inequalities, between these two kinds of measures. Further, we also state and prove inequalities connecting the classical partition-based graph entropies and partition-independent entropy measures. In addition, several explicit inequalities are derived for special classes of graphs.

摘要

在本文中,我们讨论了建立网络结构信息度量之间关系的问题。本研究考虑了两种基于熵的度量,即香农熵及其推广形式雷尼熵。我们的主要结果包括通过不等式建立这两种度量之间的形式关系。此外,我们还陈述并证明了连接基于经典划分的图熵和与划分无关的熵度量的不等式。另外,针对特殊类型的图推导了几个显式不等式。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30c6/3371044/b4780fe864b6/pone.0038159.g001.jpg

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