Self-tuning fuzzy inference based on spline function
Koji Shimojima, Toshio Fukuda, Fumihito Arai · 1994
Recently, fuzzy systems are used in many fields and places. In order to apply the fuzzy system to wider fields, it is necessary to study the tuning methods of the fuzzy system. Some self-tuning methods were proposed so far. However these conventional self-tuning methods do not have sufficient capability of generalization. In this paper, we propose new self-tuning fuzzy neural networks. The fuzzy neural networks consist of membership functions that are expressed by spline function. Delta rule is applied to tune the membership functions and consequent parts. The effectiveness of the proposed methods is shown by some numerical examples.>