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

Hu, Liang, Gao, H 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

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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.

Item Type: Article
Uncontrolled Keywords: ResPubID17723, asymptotic stability, Cohen-Grossberg neural network, time delay, parameter uncertain system, Lyapunov function, linear matrix inequality
Subjects: Historical > Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM)
Current > FOR Classification > 0906 Electrical and Electronic Engineering
Historical > SEO Classification > 970109 Expanding Knowledge in Engineering
Depositing User: VUIR
Date Deposited: 31 May 2011 04:51
Last Modified: 19 Mar 2015 06:03
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Citations in Scopus: 33 - View on Scopus

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