Building Multi-layer Small World Neural Network

Abstract

Selecting rational structure is a crucial problem on multi-layer neural network in application. In this paper a novel method is presented to solve this problem. The method breaks through the traditional methods which only determine the hidden structure and also learns the topological connectivity so that the connectivity structure has small world characteristic. The experiments show that the learned small world neural network using our method reduces the learning error and learning time but improves the generalization when compared to the networks of regular connectivity.