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Stabilization of Stochastic Perturbed Chaotic Delayed Neural Networks under Delayed Feedback Control

机译:时滞反馈控制下随机扰动混沌时滞神经网络的镇定

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This paper deals with the problem of stabilization of stochastic perturbed chaotic delayed neural networks under delayed feedback control. A delay-dependent sufficient condition for the mean-square asymptotic stability of the controlled neural network is derived via a discretized Lyapunov-Krasovskii function method. The desired feedback controller is designed in terms of linear matrix inequalities, which can be efficiently solved via standard numerical software. A numerical example illustrates the efficiency of the proposed method.
机译:本文研究了时滞反馈控制下随机扰动混沌时滞神经网络的镇定问题。通过离散化的Lyapunov-Krasovskii函数方法,得出了受控神经网络的均方渐近稳定性的依赖于延迟的充分条件。根据线性矩阵不等式设计所需的反馈控制器,可以通过标准数值软件有效地解决这些问题。数值算例说明了该方法的有效性。

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