On the learning rate analysis of a certain class of fuzzy-neural-network

Chi-Hsu Wang*, Han Leih Liu

*Corresponding author for this work

Research output: Contribution to journalConference article

Abstract

The stable learning rates for a two-layer neural network are discussed first by the Lyapunov stability theorem. This two-layer NN can then be incorporated into a fuzzy-neural-network (FNN) for a more efficient tuning process by a new genetic algorithm designed in this paper. The main contribution of this methodology is to reduce the searching time by searching only one learning rate in the FNN. All the equations for tuning both the NN and FNN are fully explained.

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