Analysis of Multilayer Neural Networks with Direct and Cross-Forward Connection

Abstract

Artificial Neural Networks are of much interest for many practical reasons. As of today, they are widely implemented. Of many possible ANNs, the most widely used one is the back-propagation model with direct connection. In this model the input layer is fed with input data and each subsequent layers are fed with the output of preceding layer. This model can be extended by feeding the input data to each layer. This article argues that this new model, named Cross Forward Connection, is optimal than the widely used Direct Connection.