%0 Journal Article
%T Stability analysis of uncertain bi-directional associative memory neural networks with variable delays<br>不确定双向联想记忆神经网络的稳定性分析
%A GUAN Huan-xin
%A WANG Zhan-shan
%A ZHANG Hua-guang
%A <br>关焕新
%A 王占山
%A 张化光
%J 控制理论与应用
%D 2008
%I 
%X The robust stability of equilibrium point is studied for bi-directional associative memory neural networks with parameter uncertainties and time-varying delays.When the activation function satisfies the condition of Lipschitz continuity,two sufficient conditions are established for the globally robust stability of the equilibrium point by suitably choosing Lyapunov-Krasovskii functional.The obtained results,which take account of the effects of neural inhibitory and excitatory on neural networks,are independent of the sizes of the time-varying delays and are easy to be checked by the interior-point algorithms in MATLAB toolbox.They are compared with prior results in a remark,and are demonstrated by two numerical examples for their effectiveness.
%K bi-directional associative memory neural networks
%K time varying delays
%K uncertainty
%K robust stability
%K linear matrix inequality(LMI)
%K Lyapunov-Krasovskii functional<br>双向联想记忆神经网络
%K 时变时滞
%K 不确定性
%K 鲁棒稳定
%K 线性矩阵不等式
%K Lyapunov-Krasovskii函数
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=1E8E5F55A3CE72D266A9956C12FEC840&yid=67289AFF6305E306&vid=C5154311167311FE&iid=38B194292C032A66&sid=65C08888CCE4801E&eid=BA48F0B914ED890A&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=14