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Dynamic analysis of reaction–diffusion Cohen–Grossberg neural networks with varying delay and Robin boundary conditions

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  • Chen, Zhang

Abstract

In this paper, reaction–diffusion Cohen–Grossberg neural networks (RDCGNN) with varying delay and Robin boundary conditions is studied by Halanay inequality and Young inequality, and sufficient conditions are given to guarantee global exponential stability of the equilibrium point. The proof of main result improves the earlier finding. Moreover, RDCGNN with large impulse also is investigated. Finally, a numerical example is given to show the effectiveness of the results in this paper.

Suggested Citation

  • Chen, Zhang, 2009. "Dynamic analysis of reaction–diffusion Cohen–Grossberg neural networks with varying delay and Robin boundary conditions," Chaos, Solitons & Fractals, Elsevier, vol. 42(3), pages 1724-1730.
    • Handle: RePEc:eee:chsofr:v:42:y:2009:i:3:p:1724-1730
    DOI: 10.1016/j.chaos.2009.03.087
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    References listed on IDEAS

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    1. Sheng, Li & Yang, Huizhong & Lou, Xuyang, 2009. "Adaptive exponential synchronization of delayed neural networks with reaction-diffusion terms," Chaos, Solitons & Fractals, Elsevier, vol. 40(2), pages 930-939.
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