Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/86111
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Type: Journal article
Title: New stability criteria for Cohen-Grossberg neural networks with time delays
Author: Hu, L.S.
Gao, H.
Shi, P.
Citation: IET Control Theory and Applications, 2009; 3(9):1275-1282
Publisher: The Institution of Engineering and Technology
Issue Date: 2009
ISSN: 1751-8644
1751-8652
Statement of
Responsibility: 
L. Hu, H. Gao, P. Shi
Abstract: The asymptotic stability is investigated for a class of time-delay Cohen-Grossberg neural networks, either with or without parameter uncertainties. By introducing a novel Lyapunov functional with the ideal of delay fractioning, a new criterion of asymptotic stability is derived in terms of a linear matrix inequality (LMI), which can be efficiently solved via standard numerical software. The criterion proves to be less conservative and the conservatism could be notably reduced by thinning the delay fractioning. Two examples are provided to demonstrate the less conservatism and effectiveness of the proposed stability conditions.
Rights: © The Institution of Engineering and Technology 2009
RMID: 0020128163
DOI: 10.1049/iet-cta.2008.0213
Appears in Collections:Electrical and Electronic Engineering publications

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