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山东大学学报(理学版) ›› 2016, Vol. 51 ›› Issue (5): 130-135.doi: 10.6040/j.issn.1671-9352.0.2015.545

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基于忆阻器的S-分布时滞随机神经网络的均方指数稳定性

王长弘,王林山*   

  1. 中国海洋大学数学科学学院, 山东 青岛 266100
  • 收稿日期:2015-11-18 出版日期:2016-05-20 发布日期:2016-05-16
  • 通讯作者: 王林山(1955— ),男,教授,博导,研究方向为动力系统与人工神经网络. E-mail:wangls@ouc.edu.cn E-mail:wchhty@qq.com
  • 作者简介:王长弘(1990— ),男,硕士研究生,研究方向为动力系统与人工神经网络. E-mail:wchhty@qq.com
  • 基金资助:
    国家自然科学基金资助项目(11171374);山东省自然科学基金重点资助项目(ZR2011AZ001)

Mean square exponential stability of memristor-based stochastic neural networks with S-type distributed delays

WANG Chang-hong, WANG Lin-shan*   

  1. School of Mathematical Science, Ocean University of China, Qingdao 266100, Shandong, China
  • Received:2015-11-18 Online:2016-05-20 Published:2016-05-16

摘要: 利用Lyapunov泛函方法及随机分析技巧,研究了基于忆阻器的S-分布时滞随机神经网络的适定性和均方指数稳定性问题,给出了稳定性判据,并仿真检验了结果的有效性。

关键词: 随机分析, Lyapunov泛函, 忆阻器神经网络, S-分布时滞, 均方指数稳定

Abstract: The mean square exponential stability of a class of memristor-based stochastic neural networks with S-type distributed delays is investigated. A criterion for the stability is given by using Lyapunov functional method and stochastic analysis technique. An example is given to show the feasibility of the theoretical results.

Key words: memristor-based neural networks, S-type distributed delays, Lyapunov functional, exponential stability in mean square, stochastic analysis

中图分类号: 

  • O175
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