Fast Learning in Neural Networks
Darryl Charles (University of Ulster, Ireland), Colin Fyfe (University of Paisley, UK), Daniel Livingstone (University of Paisley, UK) and Stephen McGlinchey (University of Paisley, UK)
Copyright: © 2008
We noted in the previous chapters that, while the multilayer perceptron is capable of approximating any continuous function, it can suffer from excessively long training times. In this chapter we will investigate methods of shortening training times for artificial neural networks using supervised learning. (Haykin, 1999) is a particularly good reference for radial basis function, RBF, networks. In this chapter we outline the theory and implementation of a RBF network before demonstrating how such a network may be used to solve one of the previously visited problems, and compare our solutions.