Delay-dependent and delay-independent stability criteria for cellular neural networks with delays

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

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  • Chuandong Li
  • Xiaofeng Liao
  • Kwok-Wo Wong


Original languageEnglish
Pages (from-to)3323-3340
Journal / PublicationInternational Journal of Bifurcation and Chaos
Issue number11
Publication statusPublished - Nov 2006


The stability issues of the equilibrium points of the cellular neural networks (CNN) with single and multiple delays are further investigated. Several novel delay-dependent and delay-independent asymptotical/exponential stability criteria are established by employing parameterized first-order model transformation, Lyapunov-Krasovskii stability theorem and LMI technique in virtue of the linearization of considered model. The stability regions with respect to the delay parameters are formulated by applying the proposed results. To the best of the authors' knowledge, few (if any) reports about such "linearization" approach to stability analysis for delayed neural network models have been presented in the open literatures. Some numerical examples are also given to illustrate the effectiveness of our results and to compare with the recent results. © World Scientific Publishing Company.

Research Area(s)

  • Cellular neural networks (CNN), Linear matrix inequalities (LMI), Lyapunov-Krasovskii functional, Parameterized first-order model transformation, Stability, Time delay