%0 Journal Article
%T Exponential stability of stochastic Hopfield neuralnetworks with distributed parameters<br>具分布参数的随机Hopfield神经网络的指数稳定(英文)
%A DENG Fei-qi
%A ZHAO Bi-rong
%A LUO Qi
%A <br>邓飞其
%A 赵碧蓉
%A 罗　琦
%J 控制理论与应用
%D 2005
%I 
%X Based on stochastic Fubini theorem,the Hopfield neural network system depicted by a stochastic partial differential equation is translated into a stochastic ordinary differential equation.By constructing a mean Lyapunov function with respect to (the space) variables and using Ito^ formula under the integral operators,the exponential stability of stochastic neutral systems with (distributed parameters) is investigated by deviating of the function along the trajectories of the systems.Also,the Lyapunov exponent estimate is obtained.Thus,the stability of stochastic systems with distributed parameters is studied by Lyapunov direct method.
%K Hopfield neural networks
%K distributed parameter
%K Lyapunov function<br>Hopfield神经网络
%K 分布参数
%K Lyapunov函数
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=E37AAC167A5CA131&yid=2DD7160C83D0ACED&vid=BC12EA701C895178&iid=0B39A22176CE99FB&sid=E0F6F365E4766526&eid=1E41DF9426604740&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=1&reference_num=16