Stability analysis for delayed cellular neural networks based on linear matrix inequality approach

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

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Author(s)

  • Xiaofeng Liao
  • Kwok-W.O. Wong
  • Shizhong Yang

Detail(s)

Original languageEnglish
Pages (from-to)3377-3384
Journal / PublicationInternational Journal of Bifurcation and Chaos in Applied Sciences and Engineering
Volume14
Issue number9
Publication statusPublished - Sep 2004

Abstract

Some sufficient conditions for the asymptotic stability of cellular neural networks with time delay are derived using the Lyapunov-Krasovskii stability theory for functional differential equations as well as the linear matrix inequality (LMI) approach. The analysis shows how some well-known results can be refined and generalized in a straightforward manner. Moreover, the stability criteria obtained are delay-independent. They are less conservative and restrictive than those reported so far in the literature, and provide a more general set of criteria for determining the stability of delayed cellular neural networks.

Research Area(s)

  • Asymptotic stability, Cellular neural networks, Linear matrix inequality, Lyapunov-Krasovskii stability theory, Time delay

Citation Format(s)

Stability analysis for delayed cellular neural networks based on linear matrix inequality approach. / Liao, Xiaofeng; Wong, Kwok-W.O.; Yang, Shizhong.

In: International Journal of Bifurcation and Chaos in Applied Sciences and Engineering, Vol. 14, No. 9, 09.2004, p. 3377-3384.

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