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Synchronization of chaotic recurrent neural networks with time-varying delays using nonlinear feedback control

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  • Cui, Baotong
  • Lou, Xuyang

Abstract

In this paper, a new method to synchronize two identical chaotic recurrent neural networks is proposed. Using the drive-response concept, a nonlinear feedback control law is derived to achieve the state synchronization of the two identical chaotic neural networks. Furthermore, based on the Lyapunov method, a delay independent sufficient synchronization condition in terms of linear matrix inequality (LMI) is obtained. A numerical example with graphical illustrations is given to illuminate the presented synchronization scheme.

Suggested Citation

  • Cui, Baotong & Lou, Xuyang, 2009. "Synchronization of chaotic recurrent neural networks with time-varying delays using nonlinear feedback control," Chaos, Solitons & Fractals, Elsevier, vol. 39(1), pages 288-294.
    • Handle: RePEc:eee:chsofr:v:39:y:2009:i:1:p:288-294
    DOI: 10.1016/j.chaos.2007.01.100
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    References listed on IDEAS

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    1. Lu, Hongtao & van Leeuwen, C., 2006. "Synchronization of chaotic neural networks via output or state coupling," Chaos, Solitons & Fractals, Elsevier, vol. 30(1), pages 166-176.
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    Cited by:

    1. Shahnazi, Reza & Haghani, Adel & Jeinsch, Torsten, 2015. "Adaptive fuzzy observer-based stabilization of a class of uncertain time-delayed chaotic systems with actuator nonlinearities," Chaos, Solitons & Fractals, Elsevier, vol. 76(C), pages 98-110.
    2. Zhang, Chaolong & Deng, Feiqi & Peng, Yunjian & Zhang, Bo, 2015. "Adaptive synchronization of Cohen–Grossberg neural network with mixed time-varying delays and stochastic perturbation," Applied Mathematics and Computation, Elsevier, vol. 269(C), pages 792-801.

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