Title :
New results on asymptotic stability analysis for static recurrent neural networks
Author :
Ma Qian ; Wang Zhen
Author_Institution :
Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China
Abstract :
This paper focuses on the asymptotic stability analysis for static recurrent neural networks. Simplified stability criteria for static neural networks are obtained and augmented Lyapunov functionals are introduced to study the delay-dependent stability for systems. Numerical examples show the improvement over approaches in the literature.
Keywords :
Lyapunov methods; asymptotic stability; delays; recurrent neural nets; Lyapunov functions; asymptotic stability analysis; delay dependent stability; static recurrent neural networks; Asymptotic stability; Biological neural networks; Delay; Recurrent neural networks; Stability criteria; Asymptotic Stability; Delay-dependent Criteria; Linear Matrix Inequality (LMIs); Static Neural Networks;
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768
