标题:Asymptotic Stability and Exponential Stability of Impulsive Delayed Hopfield Neural Networks
作者:Chen, Jing; Li, Xiaodi; Wang, Dequan
作者机构:[Chen, Jing] Shandong Univ, Dept Math, Jinan 250100, Peoples R China.; [Li, Xiaodi] Shandong Normal Univ, Sch Math Sci, Jinan 250014, Peoples R Chin 更多
通讯作者:Li, XD
通讯作者地址:[Li, XD]Shandong Normal Univ, Sch Math Sci, Jinan 250014, Peoples R China.
来源:ABSTRACT AND APPLIED ANALYSIS
出版年:2013
DOI:10.1155/2013/638496
摘要:A criterion for the uniform asymptotic stability of the equilibrium point of impulsive delayed Hopfield neural networks is presented by using Lyapunov functions and linear matrix inequality approach. The criterion is a less restrictive version of a recent result. By means of constructing the extended impulsive Halanay inequality, we also analyze the exponential stability of impulsive delayed Hopfield neural networks. Some new sufficient conditions ensuring exponential stability of the equilibrium point of impulsive delayed Hopfield neural networks are obtained. An example showing the effectiveness of the present criterion is given.
收录类别:SCOPUS;SCIE
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84885638307&doi=10.1155%2f2013%2f638496&partnerID=40&md5=ab657da93148d9b302f8fd4476a4a50a
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