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Existence and exponential stability of periodic solutions for a class of Cohen–Grossberg neural networks with time-varying delays

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  • Liu, Bingwen
  • Huang, Lihong

Abstract

In this paper, a class of Cohen–Grossberg neural networks with time-varying delays are considered. Without assuming the boundedness, monotonicity, and differentiability of activation functions and any symmetry of interconnections, sufficient conditions for the existence and exponential stability of the periodic solutions are established. This is done using the coincidence degree theorem and differential inequality techniques. The results of this paper are new and complement previously known results.

Suggested Citation

  • Liu, Bingwen & Huang, Lihong, 2007. "Existence and exponential stability of periodic solutions for a class of Cohen–Grossberg neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 32(2), pages 617-627.
    • Handle: RePEc:eee:chsofr:v:32:y:2007:i:2:p:617-627
    DOI: 10.1016/j.chaos.2005.11.009
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    Cited by:

    1. Ping, Zhao Wu & Lu, Jun Guo, 2009. "Global exponential stability of impulsive Cohen–Grossberg neural networks with continuously distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 41(1), pages 164-174.

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