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Existence and exponential stability of piecewise pseudo almost periodic solution of neutral-type inertial neural networks with mixed delay and impulsive perturbations

机译:具有混合时滞和脉冲摄动的中立型惯性神经网络分段伪几乎周期解的存在性和指数稳定性

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In this paper, the exponential stability of piecewise pseudo almost periodic solutions for neutral-type inertial neural networks with time-varying, infinite-time distributed delays (mixed delays) and impulses are investigated. First, by constructing a proper variable substitution, the original inertial neural networks can be rewritten as the first-order differential equation. Second, by using inequality techniques and Lyapunov method, some sufficient conditions which ensure the existence and exponential stability of piecewise pseudo almost periodic solutions of inertial neural networks are presented. Finally, an example with graphical illustration is given to illustrate the effectiveness of the theoretical results. (C) 2019 Published by Elsevier B.V.
机译:本文研究具有时变,无限时间分布时滞(混合时滞)和脉冲的中立型惯性神经网络的分段伪几乎周期解的指数稳定性。首先,通过构造适当的变量替换,可以将原始惯性神经网络重写为一阶微分方程。其次,通过不等式技术和Lyapunov方法,提出了一些条件,这些条件可以保证惯性神经网络的分段伪几乎周期解的存在性和指数稳定性。最后,给出了一个带有图解说明的例子来说明理论结果的有效性。 (C)2019由Elsevier B.V.发布

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