A simplified model of fuzzy inference system constructed by using RBF neurons

A new simplified model of fuzzy neural network is presented based on the functional equivalence relation between radial basis function (RBF) network and fuzzy inference system. The proposed network model has a lower number of the centre values of the network and is especially suitable for multivariable systems. An adaptive constructing method and some learning algorithms of the simplified model are proposed. The simulation results of a function mapping show that the simplified model of the fuzzy neural network has a satisfactory approximation ability to a nonlinear multivariable function.