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Attracting and invariant sets of non-autonomous reaction-diffusion neural networks with time-varying delays

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  • Long, Shujun
  • Wang, Xiaohu
  • Li, Dingshi

Abstract

In this paper, a class of non-autonomous reaction-diffusion neural networks with time-varying delays is investigated. By establishing a new differential inequality and employing the properties of spectral radius of nonnegative matrix and diffusion operator, the global attracting and positive invariant sets and exponential stability of non-autonomous reaction-diffusion neural networks with time-varying delays are obtained. Our results do not require the conditions of boundedness of the coefficient of neural networks. One example is given to illustrate the effectiveness of our conclusion.

Suggested Citation

  • Long, Shujun & Wang, Xiaohu & Li, Dingshi, 2012. "Attracting and invariant sets of non-autonomous reaction-diffusion neural networks with time-varying delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(11), pages 2199-2214.
    • Handle: RePEc:eee:matcom:v:82:y:2012:i:11:p:2199-2214
    DOI: 10.1016/j.matcom.2012.05.018
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    References listed on IDEAS

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    Cited by:

    1. Jian, Jigui & Wan, Peng, 2015. "Global exponential convergence of generalized chaotic systems with multiple time-varying and finite distributed delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 431(C), pages 152-165.

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