When is graph entropy additive? Or: Perfect couples of graphs

Janos Korner, Gabor Simonyi, Zsolt Tuza

Research output: Contribution to conferencePaper

Abstract

Summary form only given, as follows. Graph entropy is an information-theoretic functional on a graph and a probability distribution on its vertex set. Fixing the probability distribution, it is subadditive with respect to graph union. This property has been used by several authors to derive nonexistence bounds in graph covering problems. Here the authors deal with the conditions for additivity instead of subadditivity. For two complementary graphs it was proved by Csiszar et al. that additivity for every possible probability distribution is equivalent to the perfectness of the involved graph(s). Necessary and sufficient conditions of additivity (for every probability distribution) are given in full generality. This can be considered as a generalization of the concept of perfect graphs, giving some insight into the kind of graph properties to which graph entropy is sensitive.

Original languageEnglish
Number of pages1
Publication statusPublished - Dec 1 1990
Event1990 IEEE International Symposium on Information Theory - San Diego, CA, USA
Duration: Jan 14 1990Jan 19 1990

Other

Other1990 IEEE International Symposium on Information Theory
CitySan Diego, CA, USA
Period1/14/901/19/90

ASJC Scopus subject areas

  • Engineering(all)

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    Korner, J., Simonyi, G., & Tuza, Z. (1990). When is graph entropy additive? Or: Perfect couples of graphs. Paper presented at 1990 IEEE International Symposium on Information Theory, San Diego, CA, USA, .