DocumentCode
2794455
Title
A new global asymptotic stability result for delayed cellular neural networks
Author
Liu, Jing ; Zhang, Ce
Author_Institution
Dept. of Math. & Inf. Sci., Binzhou Univ., Binzhou, China
fYear
2009
fDate
17-19 June 2009
Firstpage
4061
Lastpage
4063
Abstract
This paper studies the problem of global asymptotic stability for delayed cellular neural networks(DCNNs). A new stability condition is obtained by utilizing the Lyapunov functional method and the matrix inequality approach. This condition is less restrictive and generalizes some of the previous stability results derived in the literature.
Keywords
Lyapunov methods; asymptotic stability; cellular neural nets; delays; matrix algebra; Lyapunov functional method; delayed cellular neural network; global asymptotic stability; matrix inequality approach; Asymptotic stability; Cellular networks; Cellular neural networks; Eigenvalues and eigenfunctions; Equations; Linear matrix inequalities; Mathematics; Negative feedback; Neural networks; State feedback; Delayed neural networks; Global asymptotic stability; Lyapunov functionals; Matrix inequality;
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.2009.5192532
Filename
5192532
Link To Document