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