Global exponential stability and global attractivity of impulsive Hopfield neural networks with time delays

Global exponential stability and global attractivity of impulsive Hopfield neural networks with time delays
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时滞脉冲Hopfield神经网络的全局指数稳定性和全局吸引力

DOI:
10.1016/j.cam.2009.02.094
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发表时间:
2009-09
期刊:
Journal of Computational and Applied Mathematics(美国)
影响因子:
--
通讯作者:
Xilin Fu(傅希林)
Xilin Fu(傅希林)
中科院分区:
其他
文献类型:
--
作者:
Xiaodi Li;Xilin Fu(傅希林)

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本文通过构造推广的脉冲时滞Halanay不等式,利用Lyapunov泛函方法,分析了脉冲时滞Hopfield神经网络的全局指数稳定性和全局吸引性。得到了脉冲时滞Hopfield神经网络唯一平衡点指数稳定的几个新的充分条件。这些条件在某种程度上比前面的文献中给出的条件更可行。文中还给出了一些数值算例,以说明所得结果的优越性。
In this paper, by means of constructing the extended impulsive delayed Halanay inequality and by Lyapunov functional methods, we analyze the global exponential stability and global attractivity of impulsive Hopfield neural networks with time delays. Some new sufficient conditions ensuring exponential stability of the unique equilibrium point of impulsive Hopfield neural networks with time delays are obtained. Those conditions are more feasible than that given in the earlier references to some extent. Some numerical examples are also discussed in this work to illustrate the advantage of the results we obtained.
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