NEUROCOMPUTATIONAL APPROACH TO SOLVE A CONVEXLY COMBINED FUZZY RELATIONAL EQUATION WITH GENERALIZED CONNECTIVES

Authors
CHUN MG BIEN ZN
Citation
Mg. Chun et Zn. Bien, NEUROCOMPUTATIONAL APPROACH TO SOLVE A CONVEXLY COMBINED FUZZY RELATIONAL EQUATION WITH GENERALIZED CONNECTIVES, Fuzzy sets and systems, 57(3), 1993, pp. 321-333
Citations number
17
Categorie Soggetti
Computer Sciences, Special Topics","System Science",Mathematics,"Computer Applications & Cybernetics","Statistic & Probability",Mathematics
Journal title
Fuzzy sets and systems → ACNP
ISSN journal
01650114
Volume
57
Issue
3
Year of publication
1993
Pages
321 - 333
Database
ISI
SICI code
0165-0114(1993)57:3<321:NATSAC>2.0.ZU;2-#
Abstract
In this paper, we present a method to solve a convexly combined fuzzy relational equation with generalized connectives. For this, we propose a neural network whose structure represents the fuzzy relational equa tion. Then we derive a learning algorithm by using the concept of back -propagation learning. Since the proposed method can be used for a gen eral form of fuzzy relational equations, such fuzzy max-min or min-max relational equations can be treated as its special cases.