DocumentCode :
2834849
Title :
New delay-dependent stability criterion for discrete-time recurrent neural networks with time-varying delay
Author :
Zhu, Xun-Lin ; Shang, Zhanlei ; Yang, Hong-yong
Author_Institution :
Sch. of Comput. Sci. & Commun. Eng., Zhengzhou Univ. of Light Ind., Zhengzhou, China
fYear :
2009
fDate :
17-19 June 2009
Firstpage :
4343
Lastpage :
4348
Abstract :
This paper studies the problem of stability analysis for discrete-time recurrent neural networks (DRNNs) with time-varying delays. Under a weak assumption on the activation functions, by defining a more general type of Lyapunov functionals and using a convex combination technique, a new delay-dependent stability criterion is proposed to guarantee the stability and uniqueness of equilibrium point of DRNNs in terms of linear matrix inequalities (LMIs). Compared with the existing results, the newly obtained stability condition is less conservative. A numerical example is given to illustrate the effectiveness and the benefits of the proposed method.
Keywords :
Lyapunov methods; delays; discrete time systems; linear matrix inequalities; recurrent neural nets; time-varying systems; Lyapunov functionals; convex combination technique; delay-dependent stability criterion; discrete-time recurrent neural networks; linear matrix inequalities; time-varying delay; Communication industry; Computer industry; Computer science; Delay effects; Delay estimation; Linear matrix inequalities; Neurons; Recurrent neural networks; Stability analysis; Stability criteria; Delay-dependent stability; discrete-time recurrent neural networks (DRNNs); linear matrix inequalities (LMIs); time-varying delays;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
Type :
conf
DOI :
10.1109/CCDC.2009.5194694
Filename :
5194694
Link To Document :
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