DocumentCode
2089069
Title
A new class of fuzzy neural networks with application in system modeling
Author
Ma, H. ; El-Keib, A.A. ; Ma, X.
Author_Institution
Dept. of Electr. Eng., Alabama Univ., Tuscaloosa, AL, USA
fYear
1994
fDate
10-13 Apr 1994
Firstpage
348
Lastpage
350
Abstract
This paper presents a new class of fuzzy neural networks and its application to system modeling. The optimal set of fuzzy associative memory rules and weights can be identified for a given set of sample data. Test results of modeling a nonlinear system show that the proposed fuzzy neural network can accurately model a complicated nonlinear system and the model is quite robust in the sense that its modeling accuracy is much insensitive to sample data
Keywords
digital simulation; neural nets; nonlinear systems; fuzzy associative memory rules; fuzzy neural networks; modeling accuracy; nonlinear system; sample data; system modeling; Artificial neural networks; Associative memory; Cellular neural networks; Fuzzy control; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Intelligent networks; Modeling; Nonlinear systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Southeastcon '94. Creative Technology Transfer - A Global Affair., Proceedings of the 1994 IEEE
Conference_Location
Miami, FL
Print_ISBN
0-7803-1797-1
Type
conf
DOI
10.1109/SECON.1994.324333
Filename
324333
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