Title :
Delay-dependent exponential stability of neutral neural networks with interval time-varying delay
Author :
Yajuan Liu ; Lee, S.M. ; Park, Ju H.
Author_Institution :
Sch. of Electron. Eng., Daegu Univ., Gyungsan, South Korea
Abstract :
This paper presents a global stability criteria of neural networks with neutral-type time-varying delay. By constructing a new Lyapunov-Krasovskii function, where not only upper bound, but also lower bound of time delay is included, some less conservative delay-dependent exponential stability criteria is obtained by employing new technique of dealing with some integral terms. Numerical examples are presented to demonstrate the effectiveness and improvement of our results.
Keywords :
Lyapunov methods; asymptotic stability; delays; neurocontrollers; time-varying systems; Lyapunov-Krasovskii function; delay-dependent exponential stability; interval time-varying delay; neutral neural network; Biological neural networks; Control theory; Delay effects; Delays; Stability; Upper bound; Exponential stability; Interval time-varying delay; Neutral-type neural network;
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
DOI :
10.1109/CCDC.2015.7162014