%0 Journal Article
%T New Delay-dependent Global Asymptotic Stability Condition for Hopfield Neural Networks with Time-varying Delays<br>
%A Guang-Deng Zong
%A Jia Liu
%A <br>
%J 国际自动化与计算杂志
%D 2009
%I 
%X This paper deals with the global asymptotic stability problem for Hopfield neural networks with time-varying delays. By resorting to the integral inequality and constructing a Lyapunov-Krasovskii functional, a novel delay-dependent condition is established to guarantee the existence and global asymptotic stability of the unique equilibrium point for a given delayed Hopfield neural network. This criterion is expressed in terms of linear matrix inequalities (LMIs), which can be easily checked by utilizing the recently developed algorithms for solving LMIs. Examples are provided to demonstrate the effectiveness and reduced conservatism of the proposed condition.
%K Global asymptotic stability
%K Hopfield neural networks
%K linear matrix inequality (LMI)
%K time-varying delays
%K Lyapunov-Krasovskii functional<br>
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7139AD613512F4F05F6D525B914296AA&aid=B6FEEA065F0D9CEECB1737DCA38D3F65&yid=DE12191FBD62783C&vid=B31275AF3241DB2D&iid=E158A972A605785F&sid=BFB86B6ED3A99B9D&eid=A4E67967A1AB25F0&journal_id=1476-8186&journal_name=国际自动化与计算杂志&referenced_num=0&reference_num=20