Stability of an overparametrized model

dc.contributor.authorCristi, Roberto
dc.contributor.authorFeuer, Arie
dc.contributor.departmentElectrical and Computer Engineering (ECE)en_US
dc.date.accessioned2018-02-28T20:27:45Z
dc.date.available2018-02-28T20:27:45Z
dc.date.issued1989
dc.descriptionThe article of record as published may be found at http://dx.doi.org/10.1016/0167-6911(89)90035-2
dc.description.abstractThe problem of identifying an overparametrized model is addressed in this note. It is established that when a properly initiated RLS algorithm is used with a persistently exciting external input the estimated parameters are guaranteed to converge to values representing a stabilizable model.en_US
dc.description.sponsorshipNaval Postgraduate School Direct Researchen_US
dc.description.sponsorshipFoundation for Research in Electronics, Computers and Communicationsen_US
dc.description.sponsorshipIsraeli Academy of Sciences and Humanities
dc.format.extent5 p.
dc.identifier.citationCristi, Roberto, and Arie Feuer. "Stability of an overparametrized model." Systems & control letters 13.2 (1989): 171-175.
dc.identifier.urihttps://hdl.handle.net/10945/57093
dc.publisherElsevier
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
dc.subject.authorRecursive least squares
dc.subject.authoroverparametrization
dc.subject.authorpersistently exciting stabilizable
dc.subject.authorparameter convergence
dc.titleStability of an overparametrized modelen_US
dc.typeArticle
dspace.entity.typePublication
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