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时滞Hopfield神经网络的全局指数稳定性
Global exponential stability of Hopfield neural networks with delays
【摘要】 讨论带有可变时滞的Hopfield神经网络的全局指数稳定性.在非线性激励函数满足Lipschitz条件的假设下,利用推广的Halanay不等式、Dini导数和分析技巧,建立了这类神经网络系统全局指数稳定的几个判别准则.这些判别准则仅仅依赖于系统的参数.
【Abstract】 This paper is concerned with the global stability of Hopfield neural networks with time-varying de- lays.Under assumption that the nonlinear stimulate functions are Lipschitz continuous,by means of generalized Halanay inequalities,Dini’s derivative and functional analysis techniques,several global exponential stability criteria are established,which are only dependent on the parameters of the system.
【关键词】 Hopfield神经网络;
Halanay不等式;
可变时滞;
全局指数稳定性;
【Key words】 Hopfield neural network; Halanay’s inequality; time-varying delays; globally exponential stability;
【Key words】 Hopfield neural network; Halanay’s inequality; time-varying delays; globally exponential stability;
【基金】 广州市科技计划项目(2006j1-C0341)
- 【文献出处】 纯粹数学与应用数学 ,Pure and Applied Mathematics , 编辑部邮箱 ,2008年01期
- 【分类号】O175
- 【被引频次】2
- 【下载频次】172