Modified Kolmogorov´s Neural Network in the Identification of Hammerstein and Wiener Systems

This brief deals with the possibilities of using the modified Kolmogorov´s neural network for the identification of non-linear dynamic systems, among them the Wiener and Hammerstein systems. The algorithm of training the network is simple, well convergent and with a small error of approximation. The modified neural network is characterized by a simple computer algorithm; it also omits complicated techniques of back propagation. The simulation results are shown to illustrate the modified Kolmogorov theorem.