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Adaptive exponential synchronization of delayed neural networks with reaction-diffusion terms

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  • Sheng, Li
  • Yang, Huizhong
  • Lou, Xuyang

Abstract

This paper presents an exponential synchronization scheme for a class of neural networks with time-varying and distributed delays and reaction-diffusion terms. An adaptive synchronization controller is derived to achieve the exponential synchronization of the drive-response structure of neural networks by using the Lyapunov stability theory. At the same time, the update laws of parameters are proposed to guarantee the synchronization of delayed neural networks with all parameters unknown. It is shown that the approaches developed here extend and improve the ideas presented in recent literatures.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:chsofr:v:40:y:2009:i:2:p:930-939
    DOI: 10.1016/j.chaos.2007.08.047
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    References listed on IDEAS

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    1. Yang, Yongqing & Cao, Jinde, 2007. "Exponential lag synchronization of a class of chaotic delayed neural networks with impulsive effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 386(1), pages 492-502.
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    9. Lou, Xuyang & Cui, Baotong, 2007. "Boundedness and exponential stability for nonautonomous cellular neural networks with reaction–diffusion terms," Chaos, Solitons & Fractals, Elsevier, vol. 33(2), pages 653-662.
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    Cited by:

    1. Hu, Dandan & Tan, Jieqing & Shi, Kaibo & Ding, Kui, 2022. "Switching synchronization of reaction-diffusion neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    2. 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.

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