DocumentCode
1247476
Title
Global asymptotic stability and global exponential stability of neural networks with unbounded time-varying delays
Author
Zeng, Zhigang ; Wang, Jun ; Liao, Xiaoxin
Author_Institution
Sch. of Autom., Wuhan Univ. of Technol., China
Volume
52
Issue
3
fYear
2005
fDate
3/1/2005 12:00:00 AM
Firstpage
168
Lastpage
173
Abstract
This brief studies the global asymptotic stability and the global exponential stability of neural networks with unbounded time-varying delays and with bounded and Lipschitz continuous activation functions. Several sufficient conditions for the global exponential stability and global asymptotic stability of such neural networks are derived. The new results given in the brief extend the existing relevant stability results in the literature to cover more general neural networks.
Keywords
asymptotic stability; delays; neural nets; numerical stability; activation functions; global asymptotic stability; global exponential stability; neural networks; unbounded time-varying delays; Asymptotic stability; Automation; Biological neural networks; Cellular neural networks; Delay effects; History; Neural networks; Neurons; Robust stability; Stability analysis; Global asymptotic stability; global exponential stability; neural networks; unbounded time-varying delay(UDNN);
fLanguage
English
Journal_Title
Circuits and Systems II: Express Briefs, IEEE Transactions on
Publisher
ieee
ISSN
1549-7747
Type
jour
DOI
10.1109/TCSII.2004.842047
Filename
1406210
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