Dynamic Systems Identification using Müntz Function Neural Networks with Distributed Dynamics

Abstract

This paper illustrates how the Muntz neural networks can be used effectively for identification of linear and nonlinear dynamic systems. A neuron is utilized to build the Muntz networks with locally distributed dynamics to identify input/output models of dynamic processes. For static neural network design, the orthogonal Muntz polynomials are used; for dynamic part, the orthogonal Muntz-Legendre rational functions are used