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
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;
Conference_Titel :
Intelligent Control and Information Processing (ICICIP), 2010 International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-7047-1
DOI :
10.1109/ICICIP.2010.5565281
