Title :
New condition for global asymptotically stability of cellular neural networks with time delay
Author :
Liang, Guozhuang ; Wu, Xueli ; Du, Wenxia
Author_Institution :
Coll. of Electron. Eng. & Inf., Hebei Univ. of Sci. & Technol., Shijiazhuang, China
Abstract :
Dynamical behavior of a class of neural networks with distributed delays is studied by employing suitable Lyapunov functionals, delay-dependent criteria to ensure local and global asymptotic stability of the equilibrium of the neural networks. Our results are applied to classical cellular neural networks with time delay and some novel asymptotic stability criteria are also derived. The obtained conditions are shown to be less conservative and restrictive than those reported in the known literature.
Keywords :
Lyapunov methods; asymptotic stability; cellular neural nets; delay systems; Lyapunov functional; cellular neural network; distributed delay; dynamical behavior; global asymptotically stability; time delay; Asymptotic stability; Biological neural networks; Cellular neural networks; Delay; Stability criteria; Time varying systems; LMI; Lyapunov functional; delayed cellular neural networks (DCNNs); global asymptotically stability;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5583210