Optimized Learning with Bounded Error for Feedforward Neural Networks

A learning algorithm for feedforward neural networks is presented that is based on a parameter estimation approach. The algorithm is particularly well-suited for batch learning and allows one to deal with large data sets in a computationally efficient way. An analysis of its convergence and robustness properties is made. Simulation results confirm the effectiveness of the algorithm and its advantages over learning based on backpropagation and...