Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/84787
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Type: Journal article
Title: New passivity results for uncertain discrete-time stochastic neural networks with mixed time delays
Author: Li, H.
Wang, C.
Shi, P.
Gao, H.
Citation: Neurocomputing, 2010; 73(16):3291-3299
Publisher: Elsevier
Issue Date: 2010
ISSN: 0925-2312
1872-8286
Statement of
Responsibility: 
Hongyi Li, Chuan Wang, Peng Shi, Huijun Gao
Abstract: This paper investigates the problem of passivity analysis for a class of uncertain discrete-time stochastic neural networks with mixed time delays. Here the mixed time delays are assumed to be discrete and distributed time delays and the uncertainties are assumed to be time-varying norm-bounded parameter uncertainties. By constructing a novel Lyapunov functional and introducing some appropriate free-weighting matrices, delay-dependent passivity analysis criteria are derived. Furthermore, the additional useful terms about the discrete time-varying delay will be handled by estimating the upper bound of the derivative of Lyapunov functionals, which is different from the existing passivity results. These criteria can be developed in the frame of convex optimization problems and then solved via standard numerical software. Finally, a numerical example is given to demonstrate the effectiveness of the proposed results. © 2010 Elsevier B.V.
Keywords: Distributed delays; Discrete neural networks; Passivity; Stochastic disturbances
Rights: Copyright © 2010 Elsevier B.V. All rights reserved.
DOI: 10.1016/j.neucom.2010.04.019
Appears in Collections:Aurora harvest 2
Electrical and Electronic Engineering publications

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