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New delay-dependent robust stability condition for neutral-type neural networks with mixed time delays

机译:具有混合时间延迟的中性神经网络的新延迟依赖性稳定性稳定性

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The robust exponential stability is investigated for a class of uncertain neutral-type neural networks with both variable and distributed time-varying delays. By introducing a new vector Lyapunov-Krasovskii functional, using Jensen integral inequality and linear matrix inequality (LMI) techniques, two delay-dependent sufficient criteria are obtained for exponential stability of considered neural networks, which generalize some previous results in the literature. Three examples are given to show the less conservativeness of the obtained conditions.
机译:对具有可变和分布时变延迟的一类不确定中性类型神经网络研究了鲁棒的指数稳定性。通过介绍新的Vector Lyapunov-Krasovskii功能,使用Jensen积分不等式和线性矩阵不等式(LMI)技术,获得了两个延迟相关的足够标准,用于考虑神经网络的指数稳定性,这概括了文献中的一些先前结果。给出了三种实例来显示所得条件的保守较小。

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