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具有泄漏时滞和混合加性时变时滞复数神经网络的状态估计

刘丽缤 潘和平

刘丽缤, 潘和平. 具有泄漏时滞和混合加性时变时滞复数神经网络的状态估计[J]. 应用数学和力学, 2019, 40(11): 1246-1258. doi: 10.21656/1000-0887.400174
引用本文: 刘丽缤, 潘和平. 具有泄漏时滞和混合加性时变时滞复数神经网络的状态估计[J]. 应用数学和力学, 2019, 40(11): 1246-1258. doi: 10.21656/1000-0887.400174
LIU Libin, PAN Heping. State Estimation of Complex-Valued Neural Networks With Leakage Delay and Mixed Additive Time-Varying Delays[J]. Applied Mathematics and Mechanics, 2019, 40(11): 1246-1258. doi: 10.21656/1000-0887.400174
Citation: LIU Libin, PAN Heping. State Estimation of Complex-Valued Neural Networks With Leakage Delay and Mixed Additive Time-Varying Delays[J]. Applied Mathematics and Mechanics, 2019, 40(11): 1246-1258. doi: 10.21656/1000-0887.400174

具有泄漏时滞和混合加性时变时滞复数神经网络的状态估计

doi: 10.21656/1000-0887.400174
基金项目: 国家社会科学基金(17BGL231)
详细信息
    作者简介:

    刘丽缤(1994—),女,硕士(E-mail: liulb152@163.com);潘和平(1961—),男,教授.

  • 中图分类号: O357.41

State Estimation of Complex-Valued Neural Networks With Leakage Delay and Mixed Additive Time-Varying Delays

Funds: The National Social Science Fund of China(17BGL231)
  • 摘要: 研究了具有泄漏时滞、加性离散时变时滞、加性分布时变时滞复数神经网络的状态估计问题.在复数神经网络不分解条件下, 通过构造合适的Lyapunov-Krasovskii泛函, 并应用自由权矩阵、矩阵不等式和倒数凸组合法等方法, 通过可观测的输出测量来估计神经元状态, 给出了判断误差状态模型全局渐近稳定的与时滞相关的复数线性矩阵不等式.最后, 通过一个数值仿真算例验证了理论分析的有效性.
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出版历程
  • 收稿日期:  2019-05-20
  • 修回日期:  2019-07-28
  • 刊出日期:  2019-11-01

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