Robust stability of stochastic fuzzy delayed neural networks with impulsive time window.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date:

Abstract

The urgent problem of impulsive moments which cannot be determined in advance brings new challenges beyond the conventional impulsive systems theory. In order to solve this problem, the novel concept of impulsive time window is proposed in this paper. And the stability problem of stochastic fuzzy uncertain delayed neural networks with impulsive time window is investigated. By combining the discretized Lyapunov function approach with mathematical induction method, several novel and easy-to-check sufficient conditions concerning the impulsive time window are derived to ensure that the model considered here is exponentially stable in mean square. Numerical simulations are presented to further demonstrate the effectiveness of the proposed stability criterion.

Authors

  • Xin Wang
    Key Laboratory of Bio-based Material Science & Technology (Northeast Forestry University), Ministry of Education, Harbin 150040, China.
  • Junzhi Yu
    Institute of Automation, Chinese Academy of Sciences, Beijing 100190, PR China. Electronic address: junzhi.yu@ia.ac.cn.
  • Chuandong Li
    College of Electronic and Information Engineering, Southwest University, Chongqing 400044, PR China. Electronic address: licd@cqu.edu.cn.
  • Hui Wang
    Department of Vascular Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
  • Tingwen Huang
  • Junjian Huang
    Department of Computer Science, Chongqing University of Education, Chongqing 400067, China. Electronic address: hmomu@sina.com.