DocumentCode
1155668
Title
Algebraic criteria for global exponential stability of cellular neural networks with multiple time delays
Author
Liao, Xiao-xin ; Wang, Jun
Author_Institution
Dept. of Control Sci. & Eng., Huazhong Univ. of Sci. & Technol., Hubei, China
Volume
50
Issue
2
fYear
2003
fDate
2/1/2003 12:00:00 AM
Firstpage
268
Lastpage
274
Abstract
This brief presents three sufficient conditions for the global exponential stability of cellular neural networks with time delays. The new stability results provide algebraic criteria for stability verifications and improve upon existing ones with stronger conditions. To demonstrate the differences and features of the new stability criteria, several examples are discussed to compare the present results with the existing ones.
Keywords
Lyapunov methods; asymptotic stability; cellular neural nets; delays; stability criteria; Lyapunov function; algebraic criteria; cellular neural networks; global exponential stability; multiple time delays; stability verifications; sufficient conditions; Cellular neural networks; Delay effects; Image processing; Lyapunov method; Neural networks; Nonlinear equations; Recurrent neural networks; Signal processing; Stability criteria; Sufficient conditions;
fLanguage
English
Journal_Title
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
Publisher
ieee
ISSN
1057-7122
Type
jour
DOI
10.1109/TCSI.2002.808213
Filename
1183651
Link To Document