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Stability analysis of neural networks with both variable and unbounded delays

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  • Zhao, Weirui
  • Yan, Anzhi

Abstract

In this paper, the stability of neural networks with both variable and unbounded delays is investigated. With simpler assumption that the activation functions are continuous and monotone non-decreasing, we employ homeomorphism techniques and Lyapunov functional to establish some sufficient conditions ensuring the global asymptotic stability and exponential stability of equilibrium of neural networks with both variable and unbounded delays. The new and useful results obtained in this paper extend and improve the existing ones in the previous literature.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:chsofr:v:40:y:2009:i:2:p:697-707
    DOI: 10.1016/j.chaos.2007.08.017
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    References listed on IDEAS

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    Cited by:

    1. Lan, Heng-you & Cui, Yi-Shun, 2009. "A neural network method for solving a system of linear variational inequalities," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1245-1252.

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