引用本文:邓飞其, 赵碧蓉, 罗 琦.具分布参数的随机Hopfield神经网络的指数稳定(英文)[J].控制理论与应用,2005,22(2):196~200.[点击复制]
DENG Fei-qi, ZHAO Bi-rong, LUO Qi.Exponential stability of stochastic Hopfield neuralnetworks with distributed parameters[J].Control Theory and Technology,2005,22(2):196~200.[点击复制]
具分布参数的随机Hopfield神经网络的指数稳定(英文)
Exponential stability of stochastic Hopfield neuralnetworks with distributed parameters
摘要点击 1454  全文点击 1005  投稿时间:2003-10-21  修订日期:2004-05-31
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DOI编号  
  2005,22(2):196-200
中文关键词  Hopfield神经网络  分布参数  Lyapunov函数
英文关键词  Hopfield neural networks  distributed parameter  Lyapunov function
基金项目  国家自然科学基金(60374023); 广东省自然科学基金(011629).
作者单位
邓飞其, 赵碧蓉, 罗 琦 华南理工大学 自动化科学与工程学院,广东 广州 510640 
中文摘要
      基于随机Fubini定理,将随机偏微分方程描述的Hopfield神经网络系统转化为用相应的随机常微分方程来描述.利用关于空间变量平均的Lyapunov函数与Ito^公式,通过对所构造的Lyapunov函数在Ito^微分规则下对相应系统求导的方法,获得了系统指数稳定的代数判据及其Lyapunov指数估计.实现了运用Lyapunov直接法对分布参数系统稳定性的研究.
英文摘要
      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.