An introduction to radial basis functions for system identification: a comparison with other neural network methods

Warwick, K. and Craddock, R. (1997) An introduction to radial basis functions for system identification: a comparison with other neural network methods. In: 35th IEEE Conference on Decision and Control, 11-13 Dec 1996, Kobe, Japan, pp. 464-469.

Abstract/Summary

A look is taken at the use of radial basis functions (RBFs), for nonlinear system identification. RBFs are firstly considered in detail themselves and are subsequently compared with a multi-layered perceptron (MLP), in terms of performance and usage.