Fast and robust way of learning the fourier series neural networks on the basis of multidimensional discrete fourier transform

Abstract

The calculation method for weights of orthogonal Fourier series neural networks on the grounds of multidimensional discrete Fourier transform is presented. The method proposed represents high speed of operation and outlier robustness. It allows easy reduction of network structure following its training process. The paper presents also the ways of applying the method to modelling of dynamic controlled systems. It is very easy to prepare a program which would allow to use the procedure proposed. © 2008 Springer-Verlag Berlin Heidelberg.