Modified back propagation algorithm for learning artificial neural networks

Abstract

Back Propagation is now the most widely used tool in tile field of artificial neural networks. Many attempts try to enhance this algorithm to get minimum mean square error, less training time and small number of epochs. This paper first reviews the disadvantages of the Back Propagation algorithm. Next, the new modified back propagation is explained. Finally, comparison between the two algorithms is made through many examples.