DocumentCode :
328327
Title :
Fuzzy neural networks based on spline functions
Author :
Shimojima, Koji ; Fukuda, Toshio ; Arai, Fumihito
Author_Institution :
Dept. of Mechano-Inf. & Syst., Nagoya Univ., Japan
Volume :
1
fYear :
1993
fDate :
25-29 Oct. 1993
Firstpage :
754
Abstract :
Recently, fuzzy systems are used in many fields and places. In order to apply the fuzzy systems to wider fields, it is necessary to study the tuning methods of the fuzzy system. Some self-tuning methods have been proposed so far. However these conventional self-tuning methods do not have sufficient capability of generalization. In this paper, we propose a new self-tuning fuzzy neural network. The fuzzy neural network consists of membership functions that are expressed by spline functions. The delta rule is applied to tune the membership functions and consequent parts. The effectiveness of the proposed methods is shown by some numerical examples.
Keywords :
fuzzy neural nets; generalisation (artificial intelligence); learning (artificial intelligence); self-adjusting systems; splines (mathematics); delta rule; fuzzy neural networks; generalization; learning algorithm; membership functions; self-tuning; spline function; Biomedical engineering; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Fuzzy reasoning; Fuzzy systems; Input variables; Shape; Spline; Tuning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN :
0-7803-1421-2
Type :
conf
DOI :
10.1109/IJCNN.1993.714023
Filename :
714023
Link To Document :
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