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Finite-time stability analysis of fractional-order complex-valued memristor-based neural networks with both leakage and time-varying delays

机译:基于分数阶复值忆阻器的具有泄漏和时变时延的神经网络的有限时间稳定性分析

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Finite-time stability of a class of fractional-order complex-valued memristor-based neural networks with both leakage and time-varying delays is investigated in this paper. By employing the set-valued map and differential inclusions, the solutions of memristor-based systems are intended in Filippov's sense. Via using Holder inequality, Gronwall-Bellman inequality and inequality scaling skills, sufficient conditions to guarantee the stability of the system are derived when 0 < alpha < 1/2 and 1/2 <= alpha <= 1, respectively. Finally, two numerical examples are designed to illustrate the validity and feasibility of the obtained results. (C) 2017 Elsevier B.V. All rights reserved.
机译:研究了一类同时具有泄漏和时变时滞的分数阶基于复值忆阻器的神经网络的有限时间稳定性。通过使用集值映射和微分包含,基于忆阻器的系统的解决方案在Filippov的意义上。通过使用Holder不等式,Gronwall-Bellman不等式和不等式缩放技巧,分别在0

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