Type-2 Fuzzy Neuro System Via Input-to-State-Stability Approach

Authors:
Ching-Hung Lee;Yu-Ching Lin
Affiliations:
Department of Electrical Engineering, Yuan Ze University, Chung-li, Taoyuan 320, Taiwan;Department of Electrical Engineering, Yuan Ze University, Chung-li, Taoyuan 320, Taiwan
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Year:
2007

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Abstract

This paper proposes the type-2 fuzzy neural network system (type-2 FNN) which combines the advantages of type-2 fuzzy logic systems (FLSs) and neural networks (NNs). For considering the system uncertainties, we use the type-2 FLSs to develop a type-2 FNN system. The previous results of type-1 FNN systems can be extended to a type-2 one. Furthermore, the corresponding learning algorithm is derived by input-to-state-stability (ISS) approach. Nonlinear system identification is presented to illustrate the effectiveness of our approach.