DocumentCode
2790391
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
fYear
2009
fDate
17-19 June 2009
Firstpage
3171
Lastpage
3176
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/CCDC.2009.5192315
Filename
5192315
Link To Document