DocumentCode :
1686088
Title :
Improved delay-dependent stability criterion on neural networks with time-varying delay
Author :
Zhang, Haitao ; Wang, Ting ; Fei, Shumin ; Li, Tao
Author_Institution :
Key Lab. of Meas. & Control of CSE, Southeast Univ., Nanjing, China
fYear :
2010
Firstpage :
2080
Lastpage :
2084
Abstract :
In this paper, based on Lyapunov-Krasovskii functional approach and proper integral inequality, one novel sufficient condition is derived to guarantee the global stability for neural networks with interval time-varying delay, in which the general convex combination is employed. The LMI-based criterion heavily depends on the upper and lower bounds on both time delay and its derivative, which is different from those existent ones and has wider application fields than some present results. Finally, two numerical examples can illustrate the less conservatism of the proposed methods.
Keywords :
asymptotic stability; convex programming; delays; linear matrix inequalities; neural nets; stability criteria; time-varying systems; LMI; Lyapunov Krasovskii function; convex combination; delay dependent stability criteria; integral inequality; neural network; time varying delay; Artificial neural networks; Asymptotic stability; Delay; Delay effects; Numerical stability; Stability criteria; Delayed neural networks (DNNs); LMI technique; Lyapunov-Krasovskii functional (LKF); asymptotical stability; time-varying delay;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
Type :
conf
DOI :
10.1109/WCICA.2010.5554390
Filename :
5554390
Link To Document :
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