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带脉冲的马尔科夫切换Hopfield神经网络随机均方稳定性 被引量：2

Mean Square Stability of Hopfield Neural Networks with Markovian Jump Parameters and Impulsive Effect
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摘要 本文研究了跳跃参数带有脉冲作用的Hopfield神经网络.其中跳跃参数是时间连续状态离散的马尔科夫过程.利用Lyapunov函数的方法,在不需要对激活函数作有界性,单调性和可微性的要求的基础上,考虑系统状态受脉冲作用的情况下的随机均方稳定性的判据,用线性矩阵不等式的方式给出充分条件. This paper considers stochastic mean square stability of Hopfield neural networks with Markovian jump parameters and impulsive effect. By means of Lyapunov functions , without assuming the boundedness,monotonicity and differentiability of the activation functions, a sufficient condition in terms of LMI was obtained.
作者 余瑜 董跃武 孙继涛
机构地区 同济大学数学系
出处 《生物数学学报》 CSCD 北大核心 2009年第2期265-270,共6页 Journal of Biomathematics
基金 国家自然科学基金项目(60874027)资助
关键词 HOPFIELD神经网络 马尔科夫跳跃参数 脉冲作用 LYAPUNOV函数 随机渐近稳定性 线性矩阵不等式 Hopfield neural network Markovian jump parameter impulsive effect Lyapunov function stochastic mean square stability LMI
分类号 O175 [理学—基础数学] TP183 [自动化与计算机技术—控制理论与控制工程]
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共引文献14

同被引文献16

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生物数学学报
2009年 第2期

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