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The stability of impulsive stochastic Cohen-Grossberg neural networks with mixed delays and reaction-diffusion terms

机译:具有混合时滞和反应扩散项的脉冲随机Cohen-Grossberg神经网络的稳定性

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摘要

The global asymptotic stability of impulsive stochastic Cohen-Grossberg neural networks with mixed delays and reaction-diffusion terms is investigated. Under some suitable assumptions and using Lyapunov-Krasovskii functional method, we apply the linear matrix inequality technique to propose some new sufficient conditions for the global asymptotic stability of the addressed model in the stochastic sense. The mixed time delays comprise both the time-varying and continuously distributed delays. The effectiveness of the theoretical result is illustrated by a numerical example.
机译:研究了具有混合时滞和反应扩散项的脉冲随机Cohen-Grossberg神经网络的全局渐近稳定性。在一些适当的假设下,并使用Lyapunov-Krasovskii泛函方法,我们应用线性矩阵不等式技术为随机模型中的寻址模型的全局渐近稳定性提出了一些新的充分条件。混合时间延迟包括时变和连续分布的延迟。数值例子说明了理论结果的有效性。

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