Back Propagation Learning of Neural Networks with Chaotically-Selected Affordable Neurons

Abstract

Cell assembly is one of the explanations of information processing in the brain, in which information is represented by a firing space pattern of a group of plural neurons. On the other hand, the effectiveness of neural networks has been confirmed in pattern recognition, system control, signal processing, and so on, since the backpropagation learning was proposed. In this study, we propose a new network structure with chaotically-selected affordable neurons in the hidden layer of the feedforward neural network. Computer simulated results show that the proposed network exhibits a good performance for the backpropagation learning.