Hopf bifurcation and chaos in tabu learning neuron models

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Pages (from-to)2633-2642
Journal / PublicationInternational Journal of Bifurcation and Chaos in Applied Sciences and Engineering
Volume15
Issue number8
Publication statusPublished - Aug 2005

Abstract

In this paper, we consider the nonlinear dynamical behaviors of some tabu learning neuron models. We first consider a tabu learning single neuron model. By choosing the memory decay rate as a bifurcation parameter, we prove that Hopf bifurcation occurs in the neuron. The stability of the bifurcating periodic solutions and the direction of the Hopf bifurcation are determined by applying the normal form theory. We give a numerical example to verify the theoretical analysis. Then, we demonstrate the chaotic behavior in such a neuron with sinusoidal external input, via computer simulations. Finally, we study the chaotic behaviors in tabu learning two-neuron models, with linear and quadratic proximity functions respectively. © World Scientific Publishing Company.

Research Area(s)

  • Chaos, Hopf bifurcation, Neural network, Tabu learning