具有时滞的脉冲随机神经网络的有限时间稳定性
Finite-time stability of the impulsive stochastic neural networks with delay
摘要点击 43  全文点击 54  投稿时间:2019-02-25  修订日期:2019-04-08
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DOI编号  10.7641/CTA.2019.90102
  2020,37(1):187-192
中文关键词  神经网络  脉冲  线性矩阵不等式  Lyapunov泛函  有限时间稳定
英文关键词  neural networks  impulses  linear matrix inequality  Lyapunov functional  finite-time stability.
基金项目  
学科分类代码  
作者单位E-mail
鲁成甜 安徽大学 数学科学学院 luchengtian0420@126.com 
喻圣 安徽大学 数学科学学院  
程培 安徽大学 数学科学学院 chengpei_pi@163.com 
中文摘要
      研究带有时滞的随机脉冲神经网络的有限时间稳定性问题.考虑了输入干扰型、中立型和稳定型三种类型的脉冲.通过使用Lyapunov泛函,结合线性矩阵不等式(LMIs)工具,在平均脉冲间隔定义的基础上得到系统基于矩阵不等式的有限时间稳定性充分条件,最后通过一个例子来验证结论的有效性.
英文摘要
      Focused on the problem of finite-time stability of stochastic impulsive neural networks with delay. Three types of impulses are considered: the impulses are input disturbances; the impulses are neutral type and the impulses are stabilizing. By using Lyapunov functional combined with linear matrix inequalities (LMIs) techniques, and based on the concept of the average impulsive interval the sufficient conditions for the finite-time stability are established. Fanally, a example is given to verify the effectiveness of the theoretical results.