DocumentCode
442288
Title
LMI conditions for exponential stability of neural networks with time-varying delays
Author
Yang, Haifeng ; Chu, Tianguang ; Zhang, Cishen
Author_Institution
Dept. of Mech. & Eng. Sci., Peking Univ., Beijing, China
Volume
1
fYear
2005
fDate
26-29 June 2005
Firstpage
576
Abstract
This paper presents sufficient conditions for global asymptotic/exponential stability of neural networks with time-varying delays. By using appropriate Lyapunov-Krasovskii functionals, we derive stability conditions in terms of linear matrix inequalities (LMIs). This is convenient for numerically checking the system stability using the powerful MATLAB LMI Toolbox. Compared with some earlier work, our result does not require any restriction on the derivative of the delay function. Numerical example shows the efficiency and less conservatism of the present result.
Keywords
asymptotic stability; delays; linear matrix inequalities; neural nets; time-varying systems; Lyapunov-Krasovskii functionals; asymptotic stability; exponential stability; linear matrix inequalities; neural networks; time-varying delays; Asymptotic stability; Delay effects; Image processing; Linear matrix inequalities; MATLAB; Mathematical model; Neural networks; Neurons; Sufficient conditions; Switching circuits;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Automation, 2005. ICCA '05. International Conference on
Print_ISBN
0-7803-9137-3
Type
conf
DOI
10.1109/ICCA.2005.1528184
Filename
1528184
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