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基于LMI的时滞细胞神经网络的全局渐近稳定性分析

刘德友 张建华 关新平 肖晓丹

刘德友, 张建华, 关新平, 肖晓丹. 基于LMI的时滞细胞神经网络的全局渐近稳定性分析[J]. 应用数学和力学, 2008, 29(6): 735-740.
引用本文: 刘德友, 张建华, 关新平, 肖晓丹. 基于LMI的时滞细胞神经网络的全局渐近稳定性分析[J]. 应用数学和力学, 2008, 29(6): 735-740.
LIU De-you, ZHANG Jian-hua, GUAN Xin-ping, XIAO Xiao-dan. Generalized LMI-Based Approach to the Global Asymptotic Stability of Cellular Neural Networks With Delay[J]. Applied Mathematics and Mechanics, 2008, 29(6): 735-740.
Citation: LIU De-you, ZHANG Jian-hua, GUAN Xin-ping, XIAO Xiao-dan. Generalized LMI-Based Approach to the Global Asymptotic Stability of Cellular Neural Networks With Delay[J]. Applied Mathematics and Mechanics, 2008, 29(6): 735-740.

基于LMI的时滞细胞神经网络的全局渐近稳定性分析

基金项目: 国家自然科学基金资助项目(60604004);河北省自然科学基金资助项目(F2007000637);国家杰出青年自然科学基金资助项目(60525303)
详细信息
    作者简介:

    刘德友,(1961- ),男,齐齐哈尔人,教授,博士(联系人.Tel:+86-335-8875666;E-mail:li-udeyouysu@163.com).

  • 中图分类号: TP183

Generalized LMI-Based Approach to the Global Asymptotic Stability of Cellular Neural Networks With Delay

  • 摘要: 研究了一类具有时滞的细胞神经网络的稳定性问题,利用Liapunov-Krasovskii泛函的方法,给出了时滞相关的稳定性判据.稳定性判据是以线性矩阵不等式(LMI)的形式给出,可以很容易得出时滞的上界.在得到时滞相关的稳定性判据的同时也可以得到时滞无关的稳定性判据,包含了已有文章中的很多结果.最后,数值算例说明了结果的优越性.
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    [3] Singh Vimal. A Generalized LMI-Based approach to the global asymptotic stability of cellular neural networks[J].IEEE Transaction on Neural Networks,2004,15(1):223-225. doi: 10.1109/TNN.2003.820616
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    [9] Cao J,WANG Jun.Global asymptotic stability of a general class of recurrent neural networks with time-varying delays[J].IEEE Transactions,Circuits and Systems I: Fundamental Theory and Applications,2003,50(1):34-44. doi: 10.1109/TCSI.2002.807494
    [10] 周冬明,曹进德,张立明.时滞神经网络全局渐近稳定性条件[J].应用数学和力学,2005,26(3):341-348.
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出版历程
  • 收稿日期:  2007-08-23
  • 修回日期:  2008-04-21
  • 刊出日期:  2008-06-15

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