%0 Journal Article
%T Exponential Stability in Mean Square for Stochastic Hopfield Delay Neural Networks: an LMI Approach<br>随机Hopfield时滞神经网络均方指数稳定性: LMI方法
%A Chen Wuhua
%A Lu Xiaomei
%A Li Qunhong
%A Guan Zhihong
%A <br>陈武华
%A 卢小梅
%A 李群宏
%A 关治洪
%J 数学物理学报(A辑)
%D 2007
%I 
%X By using a technique of model transformation of the system, a new type of Lyapunov functional is introduced. By applying this new Lyapunov functional, a novel delay-dependent sufficient condition of exponential stability in mean square for stochastic Hopfield delay neural networks is derived in terms of linear matrix inequalities (LMIs). A delay-independent sufficient condition is also presented. Numerical examples show that the proposed method is less conservative than the previous ones.
%K Stochastic Hopneld neural networks
%K Time-delay
%K Exponential stability in mean square
%K Linear matrix inequality (LMI)<br>随机神经网络
%K 时滞
%K 均方指数稳定性
%K 线性矩阵不等式
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=37F46C35E03B4B86&jid=4DB553CDB5F521D8C921082E5C95EC80&aid=1CFB1D17EF912377&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=CA4FD0336C81A37A&sid=91C9056D8E8856E0&eid=7555FB9CC973F695&journal_id=1003-3998&journal_name=数学物理学报(A辑)&referenced_num=0&reference_num=20