DocumentCode
582116
Title
Exponential p-stability of impulsive stochastic Cohen-Grossberg neural networks with variable coefficients and mixed delays
Author
Yao, Xiaojie ; Qin, Fajin
Author_Institution
Dept. of Math. & Comput. Sci., Liuzhou Teachers Coll., Liuzhou, China
fYear
2012
fDate
25-27 July 2012
Firstpage
3377
Lastpage
3382
Abstract
In this paper, we consider a class of impulsive stochastic Cohen-Grossberg neural networks with variable coefficients and mixed delays. By establishing an L-operator differential inequality and using stochastic analysis technique, we obtain the exponential p-stability of the impulsive stochastic cohen-Grossberg neural networks with variable coefficients and mixed delays. These results are new and generalize a few pervious known results.
Keywords
asymptotic stability; delays; neural nets; stochastic processes; L-operator differential inequality; exponential p-stability; impulsive stochastic Cohen-Grossberg neural networks; mixed delays; stochastic analysis technique; variable coefficients; Artificial neural networks; Delay; Stability analysis; Stochastic processes; Transmission line matrix methods; Vectors; Exponential p-stability; Impulsive Stochastic Cohen-Grossberg Neural Networks; L-operator Differential Inequality; Mixed Delays; Variable Coefficients;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2012 31st Chinese
Conference_Location
Hefei
ISSN
1934-1768
Print_ISBN
978-1-4673-2581-3
Type
conf
Filename
6390506
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