Modified Back Propagation Algorithm of Feed Forward Networks

The Back-propagation Neural Network (BPNN) Algorithm is widely used in solving many real time problems in world. It is highly suitable the BP learning algorithm have been reported to overcome these shortcomings. In this paper, a modified backpropagation algorithm (MBP) based on minimization of the sum of the squares of errors is proposed and implemented on benchmark XOR problem. Implementation results show that MBP outperforms standard backpropagation algorithm with respect to number of iterations and speed of connvergence.