New passivity results for uncertain discrete-time stochastic neural networks with mixed time delays

Authors:
Hongyi Li;Chuan Wang;Peng Shi;Huijun Gao
Affiliations:
Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin 150001, China;Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin 150001, China;Department of Computing and Mathematical Sciences, University of Glamorgan, Pontypridd CF37 IDL, UK and School of Engineering and Science, Victoria University, Melbourne, Vic 8001, Australia and S ...;Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin 150001, China
Venue:
Neurocomputing
Year:
2010

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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.