Ultimate boundedness of stochastic Hopfield neural networks with time-varying delays

descriptionPublicationkeyboard_double_arrow_right Article 01 Oct 2011 English Publisher:Elsevier BVJournal:Neurocomputing, volume 74, pages 2,967-2,971 (issn: 0925-2312,

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Authors: Li Wan 0003; Qinghua Zhou 0001; Pei Wang 0004;

doi: 10.1016/j.neucom.2011.04.025

Ultimate boundedness of stochastic Hopfield neural networks with time-varying delays

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Abstract

By employing Lyapunov functional theory as well as linear matrix inequalities, ultimate boundedness of stochastic Hopfield neural networks (HNN) with time-varying delays is investigated. Sufficient criteria on ultimate boundedness of stochastic HNN are firstly obtained, which fills up a gap and includes deterministic systems as our special case. Finally, numerical simulations are presented to illustrate the correctness and effectiveness of our theoretical results.

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