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A delay-dependent asymptotic stability criterion of cellular neural networks with time-varying discrete and distributed delays

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  • Park, Ju H.
  • Cho, Hyun J.

Abstract

Based on the Lyapunov functional stability analysis for differential equations and the linear matrix inequality (LMI) optimization approach, A novel criterion for the global asymptotic stability of cellular neural networks with time-varying discrete and distributed delays is derived to guarantee global asymptotic stability. The criterion is expressed in terms of LMIs, which can be solved easily by various convex optimization algorithms. Some numerical examples are given to show the effectiveness of proposed method.

Suggested Citation

  • Park, Ju H. & Cho, Hyun J., 2007. "A delay-dependent asymptotic stability criterion of cellular neural networks with time-varying discrete and distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 33(2), pages 436-442.
    • Handle: RePEc:eee:chsofr:v:33:y:2007:i:2:p:436-442
    DOI: 10.1016/j.chaos.2006.01.015
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    Cited by:

    1. Rajavel, S. & Samidurai, R. & Cao, Jinde & Alsaedi, Ahmed & Ahmad, Bashir, 2017. "Finite-time non-fragile passivity control for neural networks with time-varying delay," Applied Mathematics and Computation, Elsevier, vol. 297(C), pages 145-158.
    2. Zhao, Weirui & Yan, Anzhi, 2009. "Stability analysis of neural networks with both variable and unbounded delays," Chaos, Solitons & Fractals, Elsevier, vol. 40(2), pages 697-707.
    3. Li, Kelin & Zhang, Xinhua & Li, Zuoan, 2009. "Global exponential stability of impulsive cellular neural networks with time-varying and distributed delay," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1427-1434.
    4. Tian, Junkang & Xu, Dongsheng, 2009. "New asymptotic stability criteria for neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 41(4), pages 1916-1922.

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