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dc.rights.licenserestrictedAccess-
dc.contributor.authorFilipovic, Vojislav-
dc.date.accessioned2021-04-20T18:18:39Z-
dc.date.available2021-04-20T18:18:39Z-
dc.date.issued2017-
dc.identifier.issn0924-090X-
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/11419-
dc.description.abstract© 2017, Springer Science+Business Media B.V. This paper considers the robust recursive stochastic gradient algorithm for identification of multivariable Hammerstein model with a static nonlinear block in polynomial form and a linear block described by output-error model. The algorithm is designed for unknown parameters in vector form. It is assumed that there is a priori information about a distribution class to which a real disturbance belongs. Such class of distributions describes the presence of outliers in observations. The main contributions of the paper are: (i) design of robust stochastic approximation algorithm for MIMO Hammerstein models using robust statistics (Huber’s theory); (ii) design of general form of nonlinear block; (iii) a strong consistency of estimated parameter whereby proof is based on martingale theory, generalized strictly positive real condition and persistent excitation condition. The properties of algorithm are illustrated by simulations.-
dc.rightsinfo:eu-repo/semantics/restrictedAccess-
dc.sourceNonlinear Dynamics-
dc.titleOutlier robust stochastic approximation algorithm for identification of MIMO Hammerstein models-
dc.typearticle-
dc.identifier.doi10.1007/s11071-017-3736-2-
dc.identifier.scopus2-s2.0-85027992065-
Налази се у колекцијама:Faculty of Mechanical and Civil Engineering, Kraljevo

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