Multilayer network with bipolar weights

Abstract

A new learning algorithm for multilayer network with bipolar weights (WNBW) is presented. The learning process includes determinations of the bipolar weights of the network and the threshold values at the activation functions in each node. The resultant network performs a perfect recall for given sets of binary input and output pairs. In addition, the network can be easily implemented using digital technology for the realization of its weights.<>