Title :
Stability and periodicity of neural networks with delays and impulses
Author :
Yang, Fengjian ; Zhang, Chaolong ; Wu, Dongqing ; Yang, Jianfu ; Gao, Chuanxiang ; Liang, Lishi ; Hong, Qun
Author_Institution :
Comput. Sci. Dept., Zhongkai Univ. of Agric. & Eng., Guangzhou, China
Abstract :
This paper is concerned with the stability and periodicity for a class of impulsive neural networks with delays. By means of the Fixed point theory, Lyapunov functional and analysis technique, some sufficient conditions of exponential stability and periodicity are obtained. We can see that impulses do contribution to the stability and periodicity. An example is given to demonstrate the effectiveness of the obtained results.
Keywords :
Lyapunov methods; neural nets; Lyapunov analysis; Lyapunov functional; exponential stability; fixed point theory; impulsive neural network; sufficient condition; Cellular neural networks; Cities and towns; Delay effects; Electronic mail; Equations; Hopfield neural networks; Neural networks; Output feedback; Stability; State feedback; Fixed point; impulse; neural networks; time delays;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
DOI :
10.1109/CCDC.2009.5192315
