Title :
Criteria for exponential stability of neural networks with distributed delays
Author :
Yang, Jianfu ; Ding, Wensi ; Yang, Fengjian ; Wang, Qian ; Hu, Xiaojian ; Wu, Dongqing
Author_Institution :
Coll. of Comput. Sci., Zhongkai Univ. of Agric. & Eng., Guangzhou, China
Abstract :
In this paper, the global exponential stability is studied for a class of cellular neural networks with distributed delays. With assuming global Lipschitz conditions on the activation functions, based on the vector Lyapunov function, using the technique by virtue of Young inequality and Halanay differential inequality with delay, some sufficient conditions are obtained to ensure the uniqueness equilibrium point and globally exponential stability.
Keywords :
Lyapunov methods; asymptotic stability; cellular neural nets; delays; stability criteria; transfer functions; Halanay differential inequality; Lipschitz condition; Lyapunov function; Young inequality; activation function; cellular neural network; distributed delay; global exponential stability; stability criteria; Artificial neural networks; Asymptotic stability; Cellular neural networks; Circuit stability; Delay; Stability criteria; Lyapunov function; global exponential stability;
Conference_Titel :
Geoscience and Remote Sensing (IITA-GRS), 2010 Second IITA International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-8514-7
DOI :
10.1109/IITA-GRS.2010.5602317
