Dynamic Systems Identification using M ü ntz Function Neural Networks with Distributed Dynamics

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