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Passivity Analysis of Stochastic Memristor-Based Complex-Valued Recurrent Neural Networks with Mixed Time-Varying Delays

机译:混合时变时滞的基于忆阻器的复值递归神经网络的无源性分析

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摘要

In this paper, the passivity analysis of stochastic memristor-based complex-valued recurrent neural networks (SMCVRNNs) with discrete and distributed time-varying delays is conducted. We adopt a switched system to describe the SMCVRNN with mixed time-varying delays. Appropriate Lyapunov–Krasovski functionals are constructed to analyze the passivity of SMCVRNNs under consideration. Two sufficient conditions are presented in terms of linear matrix inequalities which assure that the SMCVRNNs are stochastically passive. The effectiveness of the obtained results is demonstrated by two examples.
机译:本文对具有离散和分布时变时滞的基于忆阻器的随机复值递归神经网络(SMCVRNN)进行了无源分析。我们采用交换系统来描述具有混合时变时延的SMCVRNN。构造了适当的Lyapunov–Krasovski函数,以分析所考虑的SMCVRNN的无源性。根据线性矩阵不等式,提供了两个充分条件,这些条件可确保SMCVRNN是随机被动的。通过两个例子证明了所获得结果的有效性。

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