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Stabilizing and synchronizing the Markovian jumping neural networks with mode-dependent mixed delays based on quantized state feedback

机译:基于量化状态反馈的依赖于模式的混合时滞稳定和同步马尔可夫跳跃神经网络

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摘要

In this paper, stabilization and synchronization control problems are considered for Markovian jumping neural networks with mode-dependent mixed time delays subject to quantization and packet dropout. By using the novel Lyapunov-Krasovskii functional, stochastic analysis technology and quantization feedback method, the stabilization problem is solved for the addressed neural networks firstly. Also, it is assumed that system state is quantized before being communicated. Then the sufficient condition for the existence of an admissible controller is established to ensure the asymptotic synchronization of the resulting closed-loop coupled neural networks. Finally, two numerical examples are presented to show the validity of our theoretical analysis results.
机译:在本文中,考虑了具有依赖于模式和混合丢包的混合时滞的马尔可夫跳跃神经网络的稳定和同步控制问题。利用新颖的Lyapunov-Krasovskii泛函,随机分析技术和量化反馈方法,首先解决了所寻址神经网络的稳定性问题。另外,假定系统状态在被通信之前被量化。然后,为允许的控制器的存在建立充分的条件,以确保所得闭环耦合神经网络的渐近同步。最后,通过两个数值例子说明了我们理论分析结果的有效性。

著录项

  • 来源
    《Journal of the Franklin Institute》 |2013年第2期|275-299|共25页
  • 作者单位

    School of Information Science and Technology, Donghua University, Shanghai 201620, PR China;

    School of Information Science and Technology, Donghua University, Shanghai 201620, PR China;

    School of Information Science and Technology, Donghua University, Shanghai 201620, PR China;

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  • 入库时间 2022-08-18 02:57:54

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