DocumentCode
2575954
Title
Globally exponential stability analysis of neural networks with distributed delays
Author
Yang, Jianfu ; Yang, Fengjian ; Li, Wei ; Zhang, Chaolong
Author_Institution
Coll. of Comput. Sci., Zhongkai Univ. of Agric. & Eng., Guangzhou, China
Volume
2
fYear
2010
fDate
28-31 Aug. 2010
Firstpage
641
Lastpage
644
Abstract
This paper analyses the existence and globally exponential stability of a class of cellular neural networks with distributed delays, with assuming global Lipschitz conditions on the activation functions, applying the idea of vector Lyapunov function, Young inequality and Halanay differential inequality with delay, some sufficient conditions are obtained to ensure the equilibrium point.
Keywords
Lyapunov methods; asymptotic stability; cellular neural nets; delays; Halanay differential inequality; Young inequality; activation functions; cellular neural networks; distributed delays; equilibrium point; global Lipschitz conditions; globally exponential stability analysis; vector Lyapunov function; Artificial neural networks; Asymptotic stability; Boolean functions; Cellular neural networks; Data structures; Delay; Stability analysis; cellular neural networks; globally exponential stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing (IITA-GRS), 2010 Second IITA International Conference on
Conference_Location
Qingdao
Print_ISBN
978-1-4244-8514-7
Type
conf
DOI
10.1109/IITA-GRS.2010.5602321
Filename
5602321
Link To Document