Title :
Global Robust Stability of Neural Networks with Both Variable and Unbounded Delays
Author :
Deng, Yanfang ; Tong, Hengqing
Author_Institution :
Dept. of Math., Wuhan Univ. of Technol., Wuhan, China
Abstract :
In this paper, global robust stability of neural networks with variable delays is studied. We employ homeomorphism techniques and Lyapunov functions to establish some sufficient conditions ensuring the global robust exponential stability and asymptotic stability of neural networks with variable delays. The new and useful results obtained in this paper extend and improve the existing ones in the previous literature.
Keywords :
Lyapunov methods; asymptotic stability; delays; neural nets; Lyapunov functions; asymptotic stability; global robust exponential stability; global robust stability; homeomorphism techniques; neural networks; sufficient conditions; unbounded delays; variable delays; Artificial neural networks; Asymptotic stability; Computer networks; Delay estimation; Electronic mail; Lyapunov method; Mathematics; Neural networks; Robust stability; Sufficient conditions; Delays; Global robust stability; Neural networks;
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
DOI :
10.1109/ICNC.2009.536
