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New Delay-Dependent Exponential H-infinity Synchronization for Uncertain Neural Networks With Mixed Time Delays

Karimi, Hamid Reza; Gao, Huijun
Journal article, Peer reviewed
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Karimi_2010_New.pdf (486.7Kb)
Contract_Karimi_2010_New.pdf (117.3Kb)
Permanent lenke
http://hdl.handle.net/11250/136757
Utgivelsesdato
2010
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  • Scientific Publications in Engineering Sciences [484]
Originalversjon
Karimi, H. R., & Gao, H. J. (2010). New Delay-Dependent Exponential H-infinity Synchronization for Uncertain Neural Networks With Mixed Time Delays. IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, 40(1), 173-185. doi: 10.1109/tsmcb.2009.2024408  
Sammendrag
This paper establishes an exponential H-infinity synchronization method for a class of uncertain master and slave neural networks (MSNNs) with mixed time delays, where the mixed delays comprise different neutral, discrete, and distributed time delays. The polytopic and the norm-bounded uncertainties are separately taken into consideration. An appropriate discretized Lyapunov-Krasovskii functional and some free-weighting matrices are utilized to establish some delay-dependent sufficient conditions for designing delayed state-feedback control as a synchronization law in terms of linear matrix inequalities under less restrictive conditions. The controller guarantees the exponential H-infinity synchronization of the two coupled MSNNs regardless of their initial states. Detailed comparisons with existing results are made, and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.
Beskrivelse
Published version of an article from the journal: IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics. Also available from the publisher: http://dx.doi.org/10.1109/tsmcb.2009.2024408. (c) 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works
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IEEE

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