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Improved exponential stability criterion for neural networks with time-varying delay.

Authors :
Liu, Xiaofan
Liu, Xinge
Tang, Meilan
Wang, Fengxian
Source :
Neurocomputing. Apr2017, Vol. 234, p154-163. 10p.
Publication Year :
2017

Abstract

In this paper, the exponential stability for a class of neural networks with time-varying delay is concerned. An improved integral inequality is derived which extends the auxiliary function-based integral inequality. A novel Lyapounov-Krasovskii functional (LKF) with some new integral terms is constructed. Based on the improved integral inequality and reciprocally convex combination approach, a less conservative exponential stability criterion for the neural networks with time-varying delay is obtained. The effectiveness of the proposed method in this paper is illustrated via numerical examples. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09252312
Volume :
234
Database :
Academic Search Index
Journal :
Neurocomputing
Publication Type :
Academic Journal
Accession number :
121242707
Full Text :
https://doi.org/10.1016/j.neucom.2016.12.057