An efficient learning algorithm for finding multiple solutions based on fixed-point homotopy method

Abstract

This paper describes an efficient learning algorithm based on fixed-point homotopy method. The proposed algorithm has the ability to train the neural networks with high success rates for the initial guesses compared with other typical second-order training algorithms. Furthermore, the method proposed here not only has the widely convergent property but also find out multiple solutions. The validity of the proposed algorithm for the standard multilayer neural networks is demonstrated through the computer simulations. As a result, it is confirmed that our algorithm is efficient and practical for the learning of the multilayer feedforward neural networks.