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事件触发下混合时滞神经网络的状态估计

杜雨薇 李兵 宋乾坤

杜雨薇, 李兵, 宋乾坤. 事件触发下混合时滞神经网络的状态估计[J]. 应用数学和力学, 2020, 41(8): 887-898. doi: 10.21656/1000-0887.400377
引用本文: 杜雨薇, 李兵, 宋乾坤. 事件触发下混合时滞神经网络的状态估计[J]. 应用数学和力学, 2020, 41(8): 887-898. doi: 10.21656/1000-0887.400377
DU Yuwei, LI Bing, SONG Qiankun. Event-Based State Estimation for Neural Network With Time-Varying Delay and Infinite-Distributed Delay[J]. Applied Mathematics and Mechanics, 2020, 41(8): 887-898. doi: 10.21656/1000-0887.400377
Citation: DU Yuwei, LI Bing, SONG Qiankun. Event-Based State Estimation for Neural Network With Time-Varying Delay and Infinite-Distributed Delay[J]. Applied Mathematics and Mechanics, 2020, 41(8): 887-898. doi: 10.21656/1000-0887.400377

事件触发下混合时滞神经网络的状态估计

doi: 10.21656/1000-0887.400377
基金项目: 国家自然科学基金(61773004);重庆市自然科学基金(cstc2019jcyjmsxmX0722);重庆市教委科技项目(KJQN201800733);重庆市留创项目(CX2018115)
详细信息
    作者简介:

    杜雨薇(1995—),女,硕士生(E-mail: 2513958654@qq.com);李兵(1980—),男,教授,博士,硕士生导师(E-mail: libingcnjy@163.com);宋乾坤(1963—),男,教授,博士,博士生导师(通讯作者. E-mail: qiankunsong@163.com).

  • 中图分类号: O357.41

Event-Based State Estimation for Neural Network With Time-Varying Delay and Infinite-Distributed Delay

Funds: The National Natural Science Foundation of China(61773004)
  • 摘要: 研究了事件触发机制下混合时滞神经网络的状态估计问题.通过引入依赖于测量输出且具有指数衰减特性的阈值函数,设计了新的事件触发机制来降低采样和通信频率.综合混合时延和事件触发特性, 建立了新的状态估计误差系统.采用Lyapunov函数和不等式技术, 建立了误差系统指数稳定性条件, 分析并排除了事件触发机制中的Zeno现象.最后通过例子验证了理论方法的有效性.
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出版历程
  • 收稿日期:  2019-12-13
  • 修回日期:  2020-01-04
  • 刊出日期:  2020-08-01

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