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The least squares algorithm, parametric system identification and bounded noise
dc.contributor.authorAkcay, Huseyinen_US
dc.contributor.authorKhargonekar, Pramod P.en_US
dc.date.accessioned2006-04-10T15:32:45Z
dc.date.available2006-04-10T15:32:45Z
dc.date.issued1993-11en_US
dc.identifier.citationAkcay, Huseyin, Khargonekar, Pramod P. (1993/11)."The least squares algorithm, parametric system identification and bounded noise." Automatica 29(6): 1535-1540. <http://hdl.handle.net/2027.42/30503>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6V21-47X254N-PJ/2/aa5122b7bb3c5d3cd465107525b6818ben_US
dc.identifier.urihttps://hdl.handle.net/2027.42/30503
dc.description.abstractThe least squares parametric system identification algorithm is analyzed assuming that the noise is a bounded signal. A bound on the worst-case parameter estimation error is derived. This bound shows that the worst-case parameter estimation error decreases to zero as the bound on the noise is decreased to zero.en_US
dc.format.extent441264 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleThe least squares algorithm, parametric system identification and bounded noiseen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelMechanical Engineeringen_US
dc.subject.hlbsecondlevelIndustrial and Operations Engineeringen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDept. of Mechanical Engineering and Applied Mechanics, The University of Michigan, Ann Arbor, MI 48109-4315, U.S.A.en_US
dc.contributor.affiliationumDept. of Electrical Engineering and Computer Science, The University of Michigan, Ann Arbor, MI 48109-2122, U.S.A.en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/30503/1/0000132.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0005-1098(93)90017-Nen_US
dc.identifier.sourceAutomaticaen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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