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Chaos synchronization of stochastic reaction-diffusion time-delay neural networks via non-fragile output-feedback control

Author

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  • Tai, Weipeng
  • Teng, Qingyong
  • Zhou, Youmei
  • Zhou, Jianping
  • Wang, Zhen

Abstract

This paper addresses the issue of non-fragile output-feedback control for master-slave chaos synchronization of reaction-diffusion time-delay neural networks subject to stochastic disturbances. Two types of norm-bounded multiplicative gain perturbations are taken into account. By the Lyapunov functional method and stochastic stability theory, a delay-independent criterion for the mean-square asymptotic synchronization of the master network and the unforced salve network is derived. It is shown that the criterion is a necessary condition of a recent delay-dependent criterion. On the basis of the proposed analysis result and with the help of some decoupling techniques, constructive approaches for the design of non-fragile output-feedback controller are developed. Finally, two examples are employed to demonstrate the applicability and low conservatism of the present analysis and design approaches.

Suggested Citation

  • Tai, Weipeng & Teng, Qingyong & Zhou, Youmei & Zhou, Jianping & Wang, Zhen, 2019. "Chaos synchronization of stochastic reaction-diffusion time-delay neural networks via non-fragile output-feedback control," Applied Mathematics and Computation, Elsevier, vol. 354(C), pages 115-127.
    • Handle: RePEc:eee:apmaco:v:354:y:2019:i:c:p:115-127
    DOI: 10.1016/j.amc.2019.02.028
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    References listed on IDEAS

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    Cited by:

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