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Global robust criteria for stochastic neutral neural networks with uncertainties and unbounded distributed delay

机译:具有不确定性和无限时滞的随机中立神经网络的全局鲁棒准则

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摘要

The problem of global robust stability analysis is studied for a class of stochastic neutral neural networks with uncertainties and unbounded distributed delay. Novel stability criteria are obtained in terms of linear matrix inequality (LMI) by employing the Lyapunov-Krasovskii functional method and using the free-weighting matrices technique. In addition, two examples are given to show the effectiveness of the obtained conditions.
机译:研究了一类具有不确定性和无穷分布时滞的随机中立神经网络的全局鲁棒稳定性分析问题。通过使用Lyapunov-Krasovskii泛函方法并使用自由加权矩阵技术,可以根据线性矩阵不等式(LMI)获得新的稳定性标准。另外,给出了两个例子来说明所获得条件的有效性。

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