New algorithms of neural fuzzy relation systems with min-implication composition

Authors:
Yanbin Luo;K. Palaniappan;Yongming Li
Affiliations:
National Laboratory of Industrial Control Technology, Institute of Modern Control Engineering, Zhejiang University, Hangzhou, China;Department of Computer Engineering and Computer Science, University of Missouri-Columbia, MO;Institute of Fuzzy Systems, College of Mathematics and Information Sciences, Shaanxi Normal University, Xi'an, China
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Year:
2005

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Abstract

Min-implication fuzzy relation equations based on Boolean-type implications can also be viewed as a way of implementing fuzzy associative memories with perfect recall. In this paper, fuzzy associative memories with perfect recall are constructed, and new on-line learning algorithms adapting the weights of its interconnections are incorporated into this neural network when the solution set of the fuzzy relation equation is non-empty. These weight matrices are actually the least solution matrix and all maximal solution matrices of the fuzzy relation equation, respectively. The complete solution set of min-implication fuzzy relation equation can be determined by the maximal solution set of this equation.