A NEW SCHEME FOR TRAINING FEEDFORWARD NEURAL NETWORKS

In this paper we present a new algorithm, which is orders of magnitude faster than the delta rule, for training feed-forward neural networks . It provides a substantial improvement over the method of Scalero and Tepedelenlioglu (IEEE Trans. Signal Process. 40(1) (1992)) in both tr aining time and numerical stability. The method combines the modified back-propagation algorithm described by Scalero and Tepedelenlioglu al ong with a faster training scheme and has better numerical stability. The algorithm is tested against other methods, and results are present ed. (C) 1997 Pattern Recognition Society.