Brief Identification of nonlinear errors-in-variables models

Authors:
I. Vajk;J. HetthéSsy
Affiliations:
Department of Automation and Applied Informatics, Budapest University of Technology and Economics, H-1521 Budapest, Hungary;Department of Automation and Applied Informatics, Budapest University of Technology and Economics, H-1521 Budapest, Hungary
Venue:
Automatica (Journal of IFAC)
Year:
2003

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Abstract

A new identification algorithm for nonlinear, but linear in parameters errors-in-variables models is presented using nonlinear, polynomial eigenvalue-eigenvector decompositions.