Constructing Iarge Back Propagation Neural Networks

摘要

Here we describe a approach for constructing large back-propagation(BP) neural networks. It is shown that this approach results in considerably less training time than conventional BP, which starts from random initial weights. An example is given in which the randomized initial weight network fails to learn, but the proposed network succeeds.