Stability analysis of high-order Hopfield-type neural networks based on a new impulsive differential inequality

Yang Liu, Rongjiang Yang, Jianquan Lu, Bo Wu, Xiushan Cai
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引用次数: 8

Abstract

This paper is devoted to studying the globally exponential stability of impulsive high-order Hopfield-type neural networks with time-varying delays. In the process of impulsive effect, nonlinear and delayed factors are simultaneously considered. A new impulsive differential inequality is derived based on the Lyapunov-Razumikhin method and some novel stability criteria are then given. These conditions, ensuring the global exponential stability, are simpler and less conservative than some of the previous results. Finally, two numerical examples are given to illustrate the advantages of the obtained results.
基于新的脉冲微分不等式的高阶hopfield型神经网络稳定性分析
研究了具有时变时滞的脉冲高阶hopfield型神经网络的全局指数稳定性。在脉冲效应过程中,同时考虑了非线性和延迟因素。基于Lyapunov-Razumikhin方法导出了一个新的脉冲微分不等式,并给出了一些新的稳定性判据。这些条件保证了全局指数稳定性,比以前的一些结果更简单,保守性更低。最后,给出了两个数值算例来说明所得结果的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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