Sequential Learning Methods on RBF with Novel Approach of Minimal Weight Update

This paper investigates sequential learning method with new form of weight update applied on a decomposed form of training algorithms using Radial Basis Function (RBF) network. Adding each basis function to the hidden layer during the course of training facilitate the weight update to be decomposed on neuron by neuron basis. A new form weight update is introduced where the weight update is based on minimal displacement of the current input elements to the elements of the nearest centre of the Gaussian neuron.