| 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] |
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| 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 1968 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) |
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| 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. |
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