DocumentCode
526805
Title
Stability analysis of higher-order recurrent neural networks with multiple delays
Author
Wang, Zhanshan ; Liu, Zhenwei ; Liu, Tao
Author_Institution
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
fYear
2010
fDate
13-15 Aug. 2010
Firstpage
526
Lastpage
531
Abstract
Global asymptotic stability problem for a class of recurrent neural networks with both high-order term and discrete delays has been studied based on delay-matrix decomposition method and linear matrix inequality technique. The proposed stability criterion extends the existing stability for the multiple delayed recurrent neural networks with higher order terms. Compared with the existing results, our results are new and easy to check.
Keywords
asymptotic stability; delays; linear matrix inequalities; recurrent neural nets; stability criteria; delay-matrix decomposition; discrete delays; global asymptotic stability problem; high-order term; higher-order recurrent neural networks; linear matrix inequality; multiple delays; stability analysis; stability criterion; Artificial neural networks; Asymptotic stability; Delay; Linear matrix inequalities; Recurrent neural networks; Stability criteria;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Information Processing (ICICIP), 2010 International Conference on
Conference_Location
Dalian
Print_ISBN
978-1-4244-7047-1
Type
conf
DOI
10.1109/ICICIP.2010.5565281
Filename
5565281
Link To Document