DocumentCode :
184094
Title :
New delay-dependent stability criteria for networks with time-varying delays
Author :
Bin Yang ; Lei Wang ; Chenxin Fan ; Min Han
Author_Institution :
Sch. of Control Sci. & Eng., Univ. of Technol., Dalian, China
fYear :
2014
fDate :
4-6 June 2014
Firstpage :
2881
Lastpage :
2886
Abstract :
This paper considers the stability of neural networks with time-varying delays. First, a new augmented Lyapunov-Krasovskii functional (LKF) including the cross terms of variables and quadratic terms multiplied by a higher degree scalar function is constructed. Second, by proposing the property of quadratic convex function and the new bounding partitioning method of activation functions which has not been proposed until now, a less conservative stability criterion expressed in the form of LMIs is presented. Finally, an example is given to illustrate the effectiveness of the proposed method.
Keywords :
Lyapunov methods; delays; linear matrix inequalities; neural nets; stability; LKF; LMI; activation functions; augmented Lyapunov-Krasovskii functional; bounding partitioning method; delay-dependent stability criteria; linear matrix inequalities; neural network stability; quadratic convex function; quadratic terms; scalar function; stability criterion; time-varying delays; Delays; Educational institutions; Neural networks; Stability criteria; Symmetric matrices; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2014
Conference_Location :
Portland, OR
ISSN :
0743-1619
Print_ISBN :
978-1-4799-3272-6
Type :
conf
DOI :
10.1109/ACC.2014.6858931
Filename :
6858931
Link To Document :
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