Sequential learning of two-layer networks with the incomplete upstart algorithm

A new procedure for the sequential learning of two layer perceptrons is presented. It improves the classical method by preventing exponential growth of output weights in most cases. Single hidden units are trained by the incomplete upstart algorithm, a new promising technique which reduces the computational effort.