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Robust Synchronization Criterion for Coupled Stochastic Discrete-Time Neural Networks with Interval Time-Varying Delays, Leakage Delay, and Parameter Uncertainties

机译:具有时变,泄漏时滞和参数不确定性的随机离散神经网络的鲁棒同步判据

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The purpose of this paper is to investigate a delay-dependent robust synchronization analysis for coupled stochastic discrete-time neural networks with interval time-varying delays in networks coupling, a time delay in leakage term, and parameter uncertainties. Based on the Lyapunov method, a new delay-dependent criterion for the synchronization of the networks is derived in terms of linear matrix inequalities (LMIs) by constructing a suitable Lyapunov-Krasovskii’s functional and utilizing Finsler’s lemma without free-weighting matrices. Two numerical examples are given to illustrate the effectiveness of the proposed methods.
机译:本文的目的是研究耦合随机随机离散时间神经网络的时滞相关鲁棒同步分析,该网络具有间隔时变的网络耦合时滞,泄漏项的时延和参数不确定性。根据Lyapunov方法,通过构造合适的Lyapunov-Krasovskii函数并利用Finsler引理,而无需使用自由加权矩阵,就可以根据线性矩阵不等式(LMI)得出一种新的依赖于延迟的网络同步准则。给出两个数值例子,说明所提方法的有效性。

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