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Almost periodic solutions of Cohen-Grossberg neural networks with time-varying delay and variable impulsive perturbations

机译:具有时变时滞和可变脉冲摄动的Cohen-Grossberg神经网络的概周期解

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In this paper, we consider the problem of existence of almost periodic solutions of impulsive Cohen-Grossberg neural networks with time-varying delays. The impulses are not at fixed moments, but are realized when the integral curves of solutions meet given hypersurfaces, i.e., the investigated model is with variable impulsive perturbations. Sufficient conditions for perfect stability of almost periodic solutions are derived. The main results are obtained by employing the Lyapunov-Razumikhin method and a comparison principle. In addition, the obtained results are extended to the uncertain case, and robust stability of almost periodic solutions is also investigated. An example is considered to demonstrate the effectiveness of our results. (c) 2019 Elsevier B.V. All rights reserved.
机译:在本文中,我们考虑具有时变时滞的脉冲Cohen-Grossberg神经网络的几乎周期解的存在性问题。脉冲不是固定的,而是在解的积分曲线遇到给定的超曲面时实现的,即所研究的模型具有可变的脉冲摄动。得出了几乎周期解的完美稳定性的充分条件。通过采用Lyapunov-Razumikhin方法和比较原理可获得主要结果。另外,将所得结果推广到不确定情况,并且还研究了几乎周期解的鲁棒稳定性。考虑一个例子来证明我们的结果的有效性。 (c)2019 Elsevier B.V.保留所有权利。

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