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State estimation for neural networks with time-varying delays in the leakage terms

机译:泄漏条款时代延迟的神经网络的状态估计

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摘要

The paper is concerned with state estimation for neural networks with time-varying delay in the leakage terms. By constructing an appropriate Lyapunov-Krasovskii functional with double integral terms, and using free-weighting matrix technique and Jensen's inequality approach, new globally asymptotic stability criteria are established. The stability criteria depend on the upper bounds of the transmission discrete time-varying delay, leakage delay as well as their derivation. The presented results can be efficiently solved by resorting to Matlab LMI Toolbox. An example is included to show the effectiveness of the proposed criteria.
机译:本文关注神经网络的状态估计,泄漏术语的时变延迟。 通过用双积分术语构建适当的Lyapunov-Krasovskii功能,并使用自由加权矩阵技术和Jensen的不等式方法,建立了新的全局渐近稳定性标准。 稳定标准取决于传输离散的时变延迟,泄漏延迟以及它们的推导的上限。 通过借助Matlab LMI工具箱,可以有效地解决所呈现的结果。 包括一个示例以显示所提出的标准的有效性。

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