A LEARNING ALGORITHM FOR FUZZY NEURAL NETWORK BASED ON NFCS FORM

Neuron-fuzzy cooperation system （NFCS） is a form of deeply combining neural network with fuzzy system. The conventional BP algorithm can be used in NFCS too, but it is bad at convergence performance. A new improved BP algorithm （NFCS-BP） is presented in allusion to fuzzy neural network based on NFCS form, which modifies not only the weights between neurons but also the compensative parameters of fuzzy logic neuron model while error is back propagating. The principle of NFCS’s cooperation and the typical construct are introduced at first, and then the iterative formula of the improved BP algorithm is derived in detail. As is pointed out by the experimented results, this algorithm is more efficient than the conventional BP algorithm on the aspects of convergence performance and the ability of function approximation.