On the learning rate analysis of a certain class of fuzzy neural network
Chi‐Hsu Wang, Han-Leih Liu · 2003
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 the 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.