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Neural Computing and Applications

, Volume 31, Issue 10, pp 6575–6586 | Cite as

New stability results for impulsive neural networks with time delays

  • Chao LiuEmail author
  • Xiaoyang Liu
  • Hongyu Yang
  • Guangjian Zhang
  • Qiong Cao
  • Junjian Huang
Original Article
  • 151 Downloads

Abstract

This paper investigates the stability of impulsive neural networks with time delays. Based on a new tool called as uniformly exponentially convergent functions, an improved Razumikhin method leads to new, more permissive stability results. By comparison with the existing results, the rigorous restrictions on impulses, which are presented in the previous Razumikhin stability theorems, are removed. Moreover, the obtained results do not restrict that the time derivative of Lyapunov function is negative definite or positive definite under the Razumikhin condition. The effectiveness of the proposed results is demonstrated by three simple numerical examples.

Keywords

Stability Impulsive neural network Razumikhin method Uniformly exponentially convergent function 

Notes

Acknowledgements

This project is supported by National Natural Science Foundation of China (Grant Nos. 61503052, 61573075, 11647097, 61603065 and 61503050), National Key R&D Program of China (Grant No. 2016YFB0100904), China Postdoctoral Science Foundation (Grant No. 2017M612911), Research Foundation of the Natural Foundation of Chongqing City (Grant No. cstc2016jcyjA0076), Scientific and Technological Research Program of Chongqing Municipal Education Commission (Grant Nos. KJ1600928 and KJ1600923) and Young Fund of Humanities and Social Sciences of the Ministry of Education of China (Grant Nos. 16JDSZ2019, 16YJC870018, 16YJC860010 and 15YJC790061).

Compliance with ethical standards

Conflict of interest

The authors declare that there is no conflict of interest regarding the publication of this paper.

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Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  • Chao Liu
    • 1
    • 2
    Email author
  • Xiaoyang Liu
    • 1
  • Hongyu Yang
    • 1
  • Guangjian Zhang
    • 1
  • Qiong Cao
    • 1
  • Junjian Huang
    • 3
  1. 1.School of Computer Science and EngineeringChongqing University of TechnologyChongqingPeople’s Republic of China
  2. 2.College of AutomationChongqing UniversityChongqingPeople’s Republic of China
  3. 3.Key laboratory of Machine Perception and Children’s Intelligence DevelopmentChongqing University of EducationChongqingPeople’s Republic of China

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