DocumentCode
2858088
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
Volume
3
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
515
Lastpage
519
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3736-8
Type
conf
DOI
10.1109/ICNC.2009.536
Filename
5365839
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