Transactions of the Institute of Systems, Control and Information Engineers
Online ISSN : 2185-811X
Print ISSN : 1342-5668
Dynamic Learning Characteristics of Chaotic Neural Networks with Stimulus-Response Scheme
Haruhiko NISHIMURANaofumi KATADA
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1997 Volume 10 Issue 10 Pages 518-527

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Abstract

In this paper, a stimulus-response scheme is proposed in chaotic neural networks with synaptic plasticities and the processes of dynamic learning under external stimuli are investigated. Owing to the refractoriness and the time-hysteresis, fixing abilities of patterns of stimuli become much higher than those based on Hopfield neural network and they also have sensitive dependences on the strength of stimulation. These characteristics turn out to be supported with the chaotic activity by examining the relation between the refractoriness and time-hysteresis, and the (maximum) Lyapunov exponent during the engraving of stimuli on the network. The above results indicate the importance of neural chaos when we try to realize the biologically relevant, real-time learning mechanism interactive with the outside, which is difficult for the Hopfield neural network showing poor response behaviors.

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