Title :
Analysis of Global Asymptotically Robust Stability about Delayed Cellular Neural Network
Author :
Wu, Xue-li ; Du, Wen-xia ; Meng, Fan-hua
Abstract :
In the paper, a novel method is proposed for global asymptotically robust stability of cellular neural networks with time-varying delay. New delay-dependent global asymptotically robust stability conditions of cellular neural network with time-varying delay is presented by constructing Lyapunov function and using linear matrix inequality (LMI). Finally, numerical example is given to demonstrate the effect of the proposed method.
Keywords :
Lyapunov methods; asymptotic stability; cellular neural nets; delays; linear matrix inequalities; Lyapunov function; delay-dependent global asymptotically robust stability condition; delayed cellular neural network; linear matrix inequality; time-varying delay; Asymptotic stability; Cellular neural networks; Computer networks; Delay effects; Electronic mail; Lyapunov method; Neural networks; Robust stability; State feedback; Sufficient conditions; LMI; Lyapunov functional; delayed cellular neural networks (DCNNs); global asymptotically robust stability;
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
DOI :
10.1109/ICNC.2009.467
