引用本文:周建平, 陈红军, 王林山.一类变时滞神经网络的全局指数稳定性[J].控制理论与应用,2007,24(3):431~434.[点击复制]
ZHOU Jian-ping, CHEN Hong-jun, WANG Lin-shan.Global exponential stability of a class of neural networks with time-varying delays[J].Control Theory and Technology,2007,24(3):431~434.[点击复制]
一类变时滞神经网络的全局指数稳定性
Global exponential stability of a class of neural networks with time-varying delays
摘要点击 1970  全文点击 1187  投稿时间：2005-12-02  修订日期：2006-07-02
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DOI编号  
  2007,24(3):431-434
中文关键词  神经网络  变时滞  全局指数稳定
英文关键词  neural networks  time-varying delays  global exponential stability
基金项目  国家自然科学基金资助项目(10171072)
作者单位
周建平, 陈红军, 王林山 安徽工业大学计算机学院, 安徽马鞍山243002
聊城大学数学科学学院, 山东聊城252059
中国海洋大学数学系, 山东青岛266071 
中文摘要
      在不要求激活函数有界的前提下, 利用Lyapunov泛函方法和线性矩阵不等式(LMI)分析技巧, 研究了一类变时滞神经网络平衡点的存在性和全局指数稳定性. 给出判别网络全局指数稳定性的判据, 推广了现有文献中的一些结果. 这些判据具有LMI的形式, 进而易于验证. 仿真例子表明了所得结果的有效性.
英文摘要
      Without assuming the boundedness of the activation functions, the existence and global exponential stability of the equilibrium point of a class of neural networks with time-varying delays is studied in this paper. By using Lyapunov functional method and linear matrix inequality (LMI) techniques, some criteria for the exponential stability of the neural networks are presented, which generalize the previous results in the literature. The criteria are easy to verify, since they take the form of LMI. An example is also given to illustrate the effectiveness of the obtained results.