Fast learning algorithms for multi-layered feedforward neural network

Abstract

In this paper, the problem of fast learning algorithm for multi-layered feedforward neural network (MLFNN) is discussed. A new fast backpropagation (FB-P) learning algorithm is proposed, By the analysis of FB-P learning algorithm, a modified FB-P (MFB-P) learning algorithm is presented. Simulations are run with the problem of XOR for B-P, FB-P and MFB-P, and the corresponding results indicate that MFB-P or FB-P converges much more quickly than B-P and MFB-P has much better generalization than FB-P or B-P.<>