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Article: Convergence rate determination for gradient-based adaptive estimators

TitleConvergence rate determination for gradient-based adaptive estimators
Authors
Bitmead, RRAnderson, BDONg, TS
KeywordsAdaptive Systems
Averaging Theory
Convergence
Parameter Estimation
Recursive Algorithms
Stochastic Systems
Issue Date1986
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/automatica
Citation
Automatica, 1986, v. 22 n. 2, p. 185-191 How to Cite?
AbstractA convergence rate estimate is derived for the homogeneous gradient-based adaptive linear estimator algorithm. This estimate involves the eigenvalues of the regression vector covariance matrix, yielding a useful measure for the choice of input signals for adaptive parameter estimation. The connection between this criterion and those more familiar from nonadaptive system identification is made and comparisons are drawn between the two areas. © 1986.
Persistent Identifierhttp://hdl.handle.net/10722/154855
ISSN
0005-1098
2021 Impact Factor: 6.150
2020 SCImago Journal Rankings: 3.132

 

DC FieldValueLanguage
dc.contributor.authorBitmead, RRen_US
dc.contributor.authorAnderson, BDOen_US
dc.contributor.authorNg, TSen_US
dc.date.accessioned2012-08-08T08:30:56Z-
dc.date.available2012-08-08T08:30:56Z-
dc.date.issued1986en_US
dc.identifier.citationAutomatica, 1986, v. 22 n. 2, p. 185-191en_US
dc.identifier.issn0005-1098en_US
dc.identifier.urihttp://hdl.handle.net/10722/154855-
dc.description.abstractA convergence rate estimate is derived for the homogeneous gradient-based adaptive linear estimator algorithm. This estimate involves the eigenvalues of the regression vector covariance matrix, yielding a useful measure for the choice of input signals for adaptive parameter estimation. The connection between this criterion and those more familiar from nonadaptive system identification is made and comparisons are drawn between the two areas. © 1986.en_US
dc.languageengen_US
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/automaticaen_US
dc.relation.ispartofAutomaticaen_US
dc.subjectAdaptive Systemsen_US
dc.subjectAveraging Theoryen_US
dc.subjectConvergenceen_US
dc.subjectParameter Estimationen_US
dc.subjectRecursive Algorithmsen_US
dc.subjectStochastic Systemsen_US
dc.titleConvergence rate determination for gradient-based adaptive estimatorsen_US
dc.typeArticleen_US
dc.identifier.emailNg, TS:tsng@eee.hku.hken_US
dc.identifier.authorityNg, TS=rp00159en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-0022681541en_US
dc.identifier.volume22en_US
dc.identifier.issue2en_US
dc.identifier.spage185en_US
dc.identifier.epage191en_US
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridBitmead, RR=7005950247en_US
dc.identifier.scopusauthoridAnderson, BDO=7404263205en_US
dc.identifier.scopusauthoridNg, TS=7402229975en_US
dc.identifier.issnl0005-1098-

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