DocumentCode :
2073501
Title :
Stability for switched Cohen-Grossberg neural networks with average dwell time
Author :
Lian Jie ; Zhang Kai ; Sun Wenan
Author_Institution :
Fac. of Electron. & Inf. Eng., Dalian Univ. of Technol., Dalian, China
fYear :
2010
fDate :
29-31 July 2010
Firstpage :
2317
Lastpage :
2322
Abstract :
This paper studies the stability of switched Cohen-Grossberg neural networks with interval time-varying delay and distributed time-varying delay. A piecewise Lyapunov function is utilized to deal with the switching problems of stability. The switching signals are arbitrary under the constraint of the average dwell time which is calculated by collecting the state decay estimation of subsystem. Sufficient conditions are obtained in terms of linear matrix inequality (LMI) to guarantee the exponential stability for the switched Cohen-Grossberg neural networks. Numerical example is provided to illustrate the effectiveness of the proposed method.
Keywords :
Lyapunov methods; asymptotic stability; delays; linear matrix inequalities; neural nets; time-varying systems; average dwell time; distributed time-varying delay; exponential stability; interval time-varying delay; linear matrix inequality; piecewise Lyapunov function; subsystem state decay estimation; switched Cohen-Grossberg neural networks; switching signals; Artificial neural networks; Delay; Stability criteria; Switched systems; Switches; Uncertainty; Average Dwell Time; Cohen-Grossberg Neural Networks; Switched Systems; Time-varying Delays;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6
Type :
conf
Filename :
5572139
Link To Document :
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