Back propagation learning of neural networks with chaotically-selected affordable neurons

— Cell assembly is one of explanations of information processing in the brain, in which an information is represented by a firing space pattern of a group of plural neurons. On the other hand, effectiveness of neural network has been confirmed in pattern recognition, system control, signal processing, and so on, since the back propagation 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 back propagation learning.

• Type: Conference
• Year: 2005
• Where: ISCAS
• Authors: Yoko Uwate, Yoshifumi Nishio
• Keywords: Feedforward Neural Network, ISCAS 2005, Neural Network, Propagation Learning