%0 Journal Article
%T Exponential stability of time-delay bi-direction associated memory neural networks in noisy environment<br>噪声环境中时滞双向联想记忆神经网络指数稳定
%A LIAO Wu-dai
%A JIAN Ji-gui
%A LIAO Xiao-xin
%A <br>廖伍代
%A 蹇继贵
%A 廖晓昕
%J 控制理论与应用
%D 2005
%I 
%X In reality,any system works in noisy environment.For bi-direction associated memory(BAM) neural networks in noisy environment,the disturbance intensity is estimated.It is the chief problem that the equilibrium of BAM neural networks should be exponentially stable.By constructing an appropriate Lyapunov function and by using It formula and M-matrix as analytic tools,the problem of exponential stability in probability one about noisy time-delay BAM neural networks is discussed,and some algebraic criteria are obtained.By those criteria,it is only necessary to verify the matrix to be M-matrix of the system's parameters,resulting in convenience in system design.The conclusions include those obtained in relevant literature as special cases.
%K bi-direction associated memory neural networks
%K stochastic system
%K It formula
%K M-matrix
%K exponential stability in probability one<br>双向联想记忆神经网络
%K 随机系统
%K It^o公式
%K M-矩阵
%K 概率1指数渐近稳定
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=EE9ABEACB492B80A&yid=2DD7160C83D0ACED&vid=BC12EA701C895178&iid=B31275AF3241DB2D&sid=54D3D9B69F1CCE77&eid=74EAF208D0F1A3E3&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=2&reference_num=8