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|Title:||New passivity results for uncertain discrete-time stochastic neural networks with mixed time delays|
|Citation:||Neurocomputing, 2010; 73(16):3291-3299|
|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.|
|Appears in Collections:||Aurora harvest 2|
Electrical and Electronic Engineering publications
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