DocumentCode
2844066
Title
Global Asymptotic Stability of Cellular Neural Networks
Author
Wang Chunmei ; Wu Xue ; Meng Hua
Author_Institution
Hebei Univ. of Sci. & Technol., Shijiazhuang, China
fYear
2009
fDate
11-13 Dec. 2009
Firstpage
1
Lastpage
4
Abstract
The global asymptotic stability problem of cellular neural networks with time delay is investigated. A new stability condition is presented based on Lyapunov-Krasovskii method, which is dependent on the size of delay. The result is given in the form of LMI, and the admitted upper bound of the delay can be obtained easily. The time delay dependent and independent results can be obtained, which include some results in the former literature. Finally, a numerical example is given to illustrate the effectiveness of the main results.
Keywords
Lyapunov matrix equations; asymptotic stability; cellular neural nets; linear matrix inequalities; Lyapunov-Krasovskii method; cellular neural networks; global asymptotic stability; linear matrix inequalities; time delay; Asymptotic stability; Cellular neural networks; Delay effects; Linear matrix inequalities; Neural networks; Neurofeedback; Output feedback; Stability criteria; Sufficient conditions; Upper bound;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4507-3
Electronic_ISBN
978-1-4244-4507-3
Type
conf
DOI
10.1109/CISE.2009.5364967
Filename
5364967
Link To Document