TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

Network classes and graph complexity measures

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoProc. - 2008 1st International Conference on Complexity and Intelligence of the Artificial and Natural Complex Systems. Medical Applications of the Complex Systems. Biomedical Computing, CANS 2008
Sivut77-84
Sivumäärä8
DOI - pysyväislinkit
TilaJulkaistu - 2008
Julkaistu ulkoisestiKyllä
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
Tapahtuma2008 1st International Conference on Complexity and Intelligence of the Artificial and Natural Complex Systems. Medical Applications of the Complex Systems. Biomedical Computing, CANS 2008 - Targu Mures, Mures, Suomi
Kesto: 8 marraskuuta 200810 marraskuuta 2008

Conference

Conference2008 1st International Conference on Complexity and Intelligence of the Artificial and Natural Complex Systems. Medical Applications of the Complex Systems. Biomedical Computing, CANS 2008
MaaSuomi
KaupunkiTargu Mures, Mures
Ajanjakso8/11/0810/11/08

Tiivistelmä

In this paper, we propose an information-theoretic approach to discriminate graph classes structurally. For this, we use a measure for determining the structural information content of graphs. This complexity measure is based on a special information functional that quantifies certain structural information of a graph. To demonstrate that the complexity measure captures structural information meaningfully, we interpret some numerical results.