Title :
Global exponential stability of cellular neural networks with time-varying delays
Author :
Yiping, Luo ; Feiqi, Deng ; Hongzhu, Yao
Author_Institution :
Coll. of Autom. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
Abstract :
The existence of equilibrium point and global exponential stability (GES) for cellular neural networks with time-varying delay are explored in this paper by applying the extended Halanay´s delay differential inequality, the theory of homotopy invariance, Dini´s derivative, and several functional analysis techniques. Some simple and new sufficient conditions are obtained to ensure existence, uniqueness of the equilibrium point and its GES of the neural networks. The results are less conservative than those established in the previous literature. In addition, this condition requires neither the active functions to be differentiable, bounded, and monotone nondecreasing nor the time-varying delays to be differentiable.
Keywords :
asymptotic stability; cellular neural nets; delays; functional analysis; Dini derivative; Halanay delay differential inequality; cellular neural networks; equilibrium point; functional analysis techniques; global exponential stability; homotopy invariance; time-varying delays; Automation; Cellular neural networks; Delay; Educational institutions; Electronic mail; Hopfield neural networks; Neural networks; Signal processing; Stability analysis; Sufficient conditions;
Conference_Titel :
Cybernetics and Intelligent Systems, 2004 IEEE Conference on
Print_ISBN :
0-7803-8643-4
DOI :
10.1109/ICCIS.2004.1460490