DocumentCode :
3284244
Title :
Stability of switched Hopfield neural networks with time-varying delay
Author :
Kai Zhang ; Jie Lian ; Xi-Ming Sun ; Dong Wang
Author_Institution :
Sch. of Electron. & Inf. Eng., Dalian Univ. of Technol., Dalian, China
fYear :
2010
fDate :
June 30 2010-July 2 2010
Firstpage :
4943
Lastpage :
4948
Abstract :
This paper considers the asymptotic stability problem for switched Hopfield neural networks with time-varying delay under hysteretic switching rule. The parameter uncertainties are considered and assumed to be norm bounded. Single Lyapunov function method is used to analyze the stability property and design the hysteretic switching rule, which is designed according to current state and the previous value of switched signal. Sufficient conditions are given in terms of linear matrix inequalities (LMIs) to guarantee the stability of the system. An example illustrates the effectiveness of the proposed theory.
Keywords :
Hopfield neural nets; Lyapunov methods; asymptotic stability; delays; linear matrix inequalities; time-varying systems; uncertain systems; asymptotic stability problem; hysteretic switching rule; linear matrix inequality; parameter uncertainty; single Lyapunov function method; switched Hopfield neural network; time varying delay; Asymptotic stability; Hopfield neural networks; Hysteresis; Linear matrix inequalities; Lyapunov method; Signal analysis; Signal design; Stability analysis; Sufficient conditions; Uncertain systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2010
Conference_Location :
Baltimore, MD
ISSN :
0743-1619
Print_ISBN :
978-1-4244-7426-4
Type :
conf
DOI :
10.1109/ACC.2010.5530932
Filename :
5530932
Link To Document :
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