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New asymptotic stability criteria for neural networks with time-varying delays

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  • Tian, Junkang
  • Xu, Dongsheng

Abstract

The problem of delay-dependent asymptotic stability criteria for neural networks (NNs) with time-varying delays is investigated. An improved linear matrix inequality-based delay-dependent stability test is introduced to ensure a large upper bound for time-delay. A new class of Lyapunov functional is constructed to derive some novel delay-dependent stability criteria. Finally, a numerical example is given to demonstrate the effectiveness of the proposed method.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:chsofr:v:41:y:2009:i:4:p:1916-1922
    DOI: 10.1016/j.chaos.2008.07.045
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    References listed on IDEAS

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    1. Singh, Vimal, 2007. "Novel LMI condition for global robust stability of delayed neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 34(2), pages 503-508.
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    2. Balasubramaniam, P. & Lakshmanan, S. & Manivannan, A., 2012. "Robust stability analysis for Markovian jumping interval neural networks with discrete and distributed time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 45(4), pages 483-495.

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