Super-Linearly Convergent BP Learning Algorithm for Feedforward Neural Networks

In this paper, some shortages of traditional BP learning algorithm are analyzed. To avoid these shortages, a modified BP learning algorithm is proposed. It is shown that this algorithm is super linearly convergent under certain conditions. This algorithm can overcome some shortages of traditional BP learning algorithm, and has the same order of computation complexity as the traditional BP algorithm. Finally, two computing examples are given. Simulation results illustrate that this algorithm is highly effective and practicable.