Existence and exponential stability of periodic solution for Cohen-Grossberg neural networks with hybrid delays

机译：混合时滞Cohen-Grossberg神经网络周期解的存在性和指数稳定性

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In this paper, a generalized model of Cohen-Grossberg neural networks with periodic coefficients and hybrid delays is investigated. By employing integro-differential inequality and M-matrix theory, some sufficient conditions ensuring the existence and global exponential stability of the periodic oscillatory solution for Cohen-Grossberg neural networks with hybrid delays are obtained. An examples is given to show the effectiveness of the obtained results.

机译：本文研究了具有周期系数和混合时滞的Cohen-Grossberg神经网络的广义模型。利用积分微分不等式和M矩阵理论，获得了具有混合时滞的Cohen-Grossberg神经网络的周期振荡解的存在性和全局指数稳定性的充分条件。举例说明了所获得结果的有效性。

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《2010 Sixth International Conference on Natural Computation》|2010年|1093-1097|共5页
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Zhang Xinhua; Li Zuoan; Li Kelin;
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正文语种
中图分类理论、方法;
关键词
Cohen-Grossberg neural networks; Periodic oscillatory solution; exponential stability; hybrid delays;

机译：Cohen-Grossberg神经网络;周期振动解;指数稳定性;混合时滞;

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Existence and exponential stability of periodic solution for Cohen-Grossberg neural networks with hybrid delays

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