DocumentCode
3057425
Title
Mean square exponential stability of stochastic cellular neural networks with time-varying delays
Author
Huang, Chuangxia ; He, Yigang ; Zhang, Ying
Author_Institution
Coll. of Math. & Comput. Sci., Changsha Univ. of Sci. & Technol., Changsha
fYear
2007
fDate
14-17 Sept. 2007
Firstpage
131
Lastpage
135
Abstract
The stability of stochastic delayed cellular neural networks (SDCNN) is investigated in this paper. With the help of Lyapunov function, a set of novel sufficient conditions on mean square exponential stability is given. A numerical example is also given to illustrate the effectiveness of our results.
Keywords
Lyapunov methods; cellular neural nets; delays; stability; stochastic systems; Lyapunov function; mean square exponential stability; stochastic cellular neural network; time-varying delay; Artificial neural networks; Biological neural networks; Cellular neural networks; Circuits; Convergence; Delay effects; Differential equations; Educational institutions; Stability; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Bio-Inspired Computing: Theories and Applications, 2007. BIC-TA 2007. Second International Conference on
Conference_Location
Zhengzhou
Print_ISBN
978-1-4244-4105-1
Electronic_ISBN
978-1-4244-4106-8
Type
conf
DOI
10.1109/BICTA.2007.4806435
Filename
4806435
Link To Document