An improved BP algorithm for pattern recognition

An improved backpropagation (BP) algorithm for pattern recognition is proposed in this paper. Using a function substitution for an error measure, it resolves the inconsistency of the BP algorithm for pattern recognition problems, i.e. the quadratic error is not sensitive to whether the training pattern is recognized correctly or not. Trained by this new method, the computer simulation result shows that the convergence speed is trebled and the performance of the network is better than the conventional BP algorithm with momentum and adaptive step size.