New stability criteria for Cohen–Grossberg neural networks with time delays

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Hu, Liang, Gao, Huijun and Shi, Peng (2009) New stability criteria for Cohen–Grossberg neural networks with time delays. IET Control Theory and Applications, 3 (9). pp. 1275-1282. ISSN 1751-8644

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.

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Item type	Article
URI	https://vuir.vu.edu.au/id/eprint/4350
DOI	10.1049/iet-cta.2008.0213
Official URL	http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arn...
Subjects	Historical > Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM) Historical > FOR Classification > 0906 Electrical and Electronic Engineering Historical > SEO Classification > 970109 Expanding Knowledge in Engineering
Keywords	ResPubID17723, asymptotic stability, Cohen-Grossberg neural network, time delay, parameter uncertain system, Lyapunov function, linear matrix inequality
Citations in Scopus	34 - View on Scopus
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