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New stability results for impulsive neural networks with time delays.

Authors :
Liu, Chao
Liu, Xiaoyang
Yang, Hongyu
Zhang, Guangjian
Cao, Qiong
Huang, Junjian
Source :
Neural Computing & Applications. Oct2019, Vol. 31 Issue 10, p6575-6586. 12p.
Publication Year :
2019

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09410643
Volume :
31
Issue :
10
Database :
Academic Search Index
Journal :
Neural Computing & Applications
Publication Type :
Academic Journal
Accession number :
139232494
Full Text :
https://doi.org/10.1007/s00521-018-3481-6