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广义Hopfield神经网络的绝对指数稳定性

文海霞 黄丽湘 张继业

文海霞, 黄丽湘, 张继业. 广义Hopfield神经网络的绝对指数稳定性[J]. 西南交通大学学报, 2007, 20(5): 583-588.
引用本文: 文海霞, 黄丽湘, 张继业. 广义Hopfield神经网络的绝对指数稳定性[J]. 西南交通大学学报, 2007, 20(5): 583-588.
WEN Haixia, HUANG Lixiang, ZHANG Jiye. Absolute Exponential Stability of Generalized Hopfield Neural Networks[J]. Journal of Southwest Jiaotong University, 2007, 20(5): 583-588.
Citation: WEN Haixia, HUANG Lixiang, ZHANG Jiye. Absolute Exponential Stability of Generalized Hopfield Neural Networks[J]. Journal of Southwest Jiaotong University, 2007, 20(5): 583-588.

广义Hopfield神经网络的绝对指数稳定性

基金项目: 

新世纪优秀人才支持计划项目(NCET-04-0889)

四川省青年科技基金项目(05ZQ026-015)

详细信息
    作者简介:

    文海霞(1977- ),女,讲师,研究方向为动力系统稳定性与控制,E-mail:whxgyzheng@163.com

    通讯作者:

    张继业(1965- ),男,教授,博士,研究方向为稳定性理论,流固耦合振动,车辆动力学,电话:028-87634355, E-mail:yzhang@home.swjtu.edu.cn

Absolute Exponential Stability of Generalized Hopfield Neural Networks

  • 摘要: 研究了一类广义神经网络系统平衡点的存在性、唯一性和绝对指数稳定性.这类神经网络包含Hopfield神经网络和细胞型神经网络,不要求激活函数可微和有界.应用拓扑理论,得到了广义Hopfield神经网络平衡点的存在性和唯一性的充分必要条件;利用矩阵的性质,通过构造Lurie型Liapunov函数,得到了广义Hopfield神经网络绝对指数稳定的充分条件以及几类特殊神经网络绝对指数稳定的充分必要条件.

     

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出版历程
  • 收稿日期:  2006-12-08
  • 刊出日期:  2007-10-25

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