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全局渐近稳定的一类变时多时滞神经网络模型
引用本文:王姗姗,王拉省.全局渐近稳定的一类变时多时滞神经网络模型[J].纺织高校基础科学学报,2008,21(3):342-345.
作者姓名:王姗姗  王拉省
作者单位:西安工程大学,理学院,陕西,西安,710048
基金项目:西安工程大学校管项目 
摘    要:研究了一类变时滞神经网络的渐近稳定性问题.利用线性矩阵不等式和构造适当的Lya-punov函数,给出了该模型的平衡点惟一性和全局渐近稳定的新判据.与现有的一些文献中的结果相比,考虑了神经元激励和抑制的影响,所得的判据保守性小,适用范围宽.

关 键 词:神经网络  变时滞  多时滞  Lyapunov函数

Global asymptotic stability of a class of neural networks with multiple time-varying delays
WANG Shan-shan,WANG La-sheng.Global asymptotic stability of a class of neural networks with multiple time-varying delays[J].Basic Sciences Journal of Textile Universities,2008,21(3):342-345.
Authors:WANG Shan-shan  WANG La-sheng
Affiliation:WANG Shan-shan, WANG La-sheng (School of Science, Xi'an Polytechnic University, Xi'an 710048,China)
Abstract:Global asymptotical stability of a class of neural networks with multiple time-varying delays was studied.On the basis of LMI inequality technique and properly built Lyapunov function,a new sufficient criteria is given to ensure the global asymptotical stability for the equilibrium points in relevant neural networks.Compared with some results in earlier works,the obtained criteria are less conservative and wider in application,and can eliminate the difference between the neuronal excitatory and inhibitory effects.
Keywords:neural networks  time-varying delays  multiple delays  Lyapunov function
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