Convergence of powers of a max-convex mean fuzzy matrix

Yung Yin Lur, Yan Kuen Wu, Sy Ming Guu*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Fuzzy matrices provide convenient representations for fuzzy relations on finite universes. In the literature, the behavior of powers of a fuzzy matrix with max-min/max-product/max-Archimedean t-norm/max-t-norm compositions have been studied. Conventionally, the algebraic operations involved in the study of powers of a fuzzy matrix usually belong to the max-t-norms. Recently the powers of a max-arithmetic mean fuzzy matrix have been studied. Typically, the max-arithmetic mean operation is not a max-t-norm. Since the max-arithmetic mean is a special example of the max-convex mean operations, we shall extend the study to powers of a max-convex mean fuzzy matrix in this paper. We show that its powers are always convergent.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008
Pages562-566
Number of pages5
DOIs
StatePublished - 2008
Externally publishedYes
Event2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008 - Hong Kong, China
Duration: 01 06 200806 06 2008

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Conference

Conference2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008
Country/TerritoryChina
CityHong Kong
Period01/06/0806/06/08

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