An analytical approach based on information theory for neural network architecture

Abstract

In this study on the neural network architecture following its training period, with only one hidden layer and some constraints, the number of hidden nodes have been calculated by using the concepts of mean information quantity which was defined as an entropy, and the importance of sigmoid function has been emphasized as the necessary condition of analytical approach used.