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
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;
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.2009.5192532
