DocumentCode :
3423448
Title :
An intuitionistic fuzzy associative memory network and its learning rule
Author :
Li, Long ; Yang, Jie ; Wu, Wei ; Wu, Tianshuang
Author_Institution :
Sch. of Math. Sci., Dalian Univ. of Technol., Dalian, China
fYear :
2009
fDate :
17-19 Aug. 2009
Firstpage :
350
Lastpage :
353
Abstract :
Intuitionistic fuzzy set (IFS) is a generalization of fuzzy set by introducing an additional attribute parameter called non-membership degree. In this paper, an intuitionistic fuzzy associative memory (IFAM) network is proposed by combining IFS with associative memory network. Based on Goumldel fuzzy implication operator and its dual fuzzy co-implication operator, a learning rule for multiple intuitionistic fuzzy pattern pairs in IFAM is presented. The storage capacity of IFAM is also investigated. It is shown that under certain conditions, the proposed rule can efficiently encode multiple intuitionistic fuzzy pattern pairs into a single IFAM and achieve perfect association of these pairs.
Keywords :
content-addressable storage; fuzzy set theory; Godel fuzzy implication operator; attribute parameter; dual fuzzy coimplication operator; fuzzy set generalization; intuitionistic fuzzy associative memory network; learning rule; nonmembership degree; storage capacity; Artificial neural networks; Associative memory; Decision making; Fuzzy control; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Hybrid intelligent systems; Mathematics; Pattern recognition; Gödel dual fuzzy co-implication operator; Gödel fuzzy implication operator; Intuitionistic fuzzy sets; intuitionistic fuzzy associative memory; perfect association;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Granular Computing, 2009, GRC '09. IEEE International Conference on
Conference_Location :
Nanchang
Print_ISBN :
978-1-4244-4830-2
Type :
conf
DOI :
10.1109/GRC.2009.5255096
Filename :
5255096
Link To Document :
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