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Exponential Stability Of Impulsive Cohen-grossberg Neural Networks With Time-varying Delays And Reaction-diffusion Terms

机译:时变时滞和反应扩散项的脉冲Cohen-Grossberg神经网络的指数稳定性

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摘要

In this paper, we investigate a class of impulsive Cohen-Grossberg neural networks with time-varying delays and reaction-diffusion terms. By establishing a delay differential inequality with impulsive initial conditions and employing M-matrix theory, we find some sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for impulsive Cohen-Grossberg neural networks with time-varying delays and reaction-diffusion terms. In particular, the estimate of the exponential convergence rate is also provided, which depends on the system parameters and delays. Two examples are given to illustrate the results obtained here.
机译:在本文中,我们研究了一类具有时变时滞和反应扩散项的脉冲Cohen-Grossberg神经网络。通过建立具有脉冲初始条件的时滞微分不等式并运用M-矩阵理论,我们找到了一些充分的条件,以确保时变时滞和反应扩散的脉冲Cohen-Grossberg神经网络平衡点的存在,唯一性和全局指数稳定性。条款。特别地,还提供了指数收敛速率的估计,该估计取决于系统参数和延迟。给出两个例子来说明这里获得的结果。

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