Simplification of fuzzy-neural systems using similarity analysis

This paper presents a fuzzy neural network system (FNNS) for implementing fuzzy inference systems. In the FNNS, a fuzzy similarity measure for fuzzy rules is proposed to eliminate redundant fuzzy logical rules, so that the number of rules in the resulting fuzzy inference system will be reduced. Moreover, a fuzzy similarity measure for fuzzy sets that indicates the degree to which two fuzzy sets are equal is applied to combine similar input linguistic term nodes. Thus we obtain a method for reducing the complexity of a fuzzy neural network. We also design a new and efficient on-line initialization method for choosing the initial parameters of the FNNS. A computer simulation is presented to illustrate the performance and applicability of the proposed FNNS. The result indicates that the FNNS still has desirable performance under fewer fuzzy logical rules and adjustable parameters.

[1]  Sankar K. Pal,et al.  Fuzzy Mathematical Approach to Pattern Recognition , 1986 .

[2]  Li-Xin Wang,et al.  Adaptive fuzzy systems and control - design and stability analysis , 1994 .

[3]  M. Roubens.  Pattern classification problems and fuzzy sets , 1978 .

[4]  James M. Keller,et al.  A new approach to inference in approximate reasoning , 1991 .

[5]  James M. Keller,et al.  Neural network implementation of fuzzy logic , 1992 .

[6]  Kwang Y. Lee,et al.  Diagonal recurrent neural networks for dynamic systems control , 1995, IEEE Trans. Neural Networks.

[7]  Yoshiki Uchikawa,et al.  On fuzzy modeling using fuzzy neural networks with the back-propagation algorithm , 1992, IEEE Trans. Neural Networks.

[8]  Z. Zenn Bien,et al.  A dynamic gesture recognition system for the Korean sign language (KSL) , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[9]  Frank L. Lewis,et al.  Some issues about fuzzy logic control , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[10]  E. Backer,et al.  Cluster analysis by optimal decomposition of induced fuzzy sets , 1978 .

[11]  Richard D. Braatz,et al.  On the "Identification and control of dynamical systems using neural networks" , 1997, IEEE Trans. Neural Networks.

[12]  Chin-Teng Lin,et al.  A neural fuzzy control system with structure and parameter learning , 1995 .

[13]  Yong-Zai Lu,et al.  Fuzzy Model Identification and Self-Learning for Dynamic Systems , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[14]  Chuen-Chien Lee.  FUZZY LOGIC CONTROL SYSTEMS: FUZZY LOGIC CONTROLLER - PART I , 1990 .

[15]  Chin-Teng Lin,et al.  Neural-Network-Based Fuzzy Logic Control and Decision System , 1991, IEEE Trans. Computers.

[16]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..