DocumentCode
480232
Title
Global Exponential Stability of Fuzzy Cellular Neural Networks with Mixed Delays
Author
Wu, Ranchao ; Chen, Liping
Author_Institution
Sch. of Math., Anhui Univ., Hefei
Volume
4
fYear
2008
fDate
12-14 Dec. 2008
Firstpage
867
Lastpage
870
Abstract
In this paper, a class of fuzzy cellular neural networks with mixed delays is studied. By using the fixed point theorem, M-matrix theory and some analytic techniques, sufficient conditions for the existence and global exponential stability of the unique equilibrium point are obtained. For illustration, an example is given to show the effectiveness of the obtained results.
Keywords
asymptotic stability; cellular neural nets; delays; fuzzy neural nets; matrix algebra; M-matrix theory; fixed point theorem; fuzzy cellular neural network; global exponential stability; mixed delay; Cellular neural networks; Delay; Feeds; Fuzzy logic; Fuzzy neural networks; Mathematics; Neurofeedback; Stability analysis; State feedback; Sufficient conditions;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location
Wuhan, Hubei
Print_ISBN
978-0-7695-3336-0
Type
conf
DOI
10.1109/CSSE.2008.707
Filename
4722756
Link To Document