A fast hierarchical neural network for pattern classification

Abstract

A fast hierarchical neural network pattern classifier is proposed in this paper for pattern classification. It is trained with the multilayer perceptron algorithm. It uses only boundary pattern samples and consists of two stages. The first stage provides an approximate solution whereas the second stage gives the exact solution. The experimental results show that the learning time required for the proposed hierarchical network is much less than the standard multilayer perceptron classifier. >