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Article: ON OPTIMAL CHOICE OF SAMPLING STRATEGIES FOR LINEAR SYSTEM IDENTIFICATION.

TitleON OPTIMAL CHOICE OF SAMPLING STRATEGIES FOR LINEAR SYSTEM IDENTIFICATION.
Authors
Issue Date1976
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/00207179.asp
Citation
International Journal Of Control, 1976, v. 23 n. 4, p. 459-475 How to Cite?
AbstractThe effect of the sampling strategy on the achievable accuracy in linear system identification experiments is presented and the effect of having different sampling rates in each of the subexperiments is investigated. It is shown that the optimal information return can be achieved by use of a finite number of subexperiments. The theory is developed in two parts: the first relating to the identification of a stochastic process from output observations; the second relating to the identification of an input-output transfer function from noisy observations. Examples show that the appropriate choice of sampling strategy can be of paramount importance in identification experiments. The design can be extended in a straightforward manner to safeguard against a single noninformative experiment in the case of diffuse prior distribution for the parameters.
Persistent Identifierhttp://hdl.handle.net/10722/154788
ISSN
2015 Impact Factor: 1.88
2015 SCImago Journal Rankings: 1.494

 

DC FieldValueLanguage
dc.contributor.authorNg, Tung Sangen_US
dc.contributor.authorGoodwin, Graham Clifforden_US
dc.date.accessioned2012-08-08T08:30:39Z-
dc.date.available2012-08-08T08:30:39Z-
dc.date.issued1976en_US
dc.identifier.citationInternational Journal Of Control, 1976, v. 23 n. 4, p. 459-475en_US
dc.identifier.issn0020-7179en_US
dc.identifier.urihttp://hdl.handle.net/10722/154788-
dc.description.abstractThe effect of the sampling strategy on the achievable accuracy in linear system identification experiments is presented and the effect of having different sampling rates in each of the subexperiments is investigated. It is shown that the optimal information return can be achieved by use of a finite number of subexperiments. The theory is developed in two parts: the first relating to the identification of a stochastic process from output observations; the second relating to the identification of an input-output transfer function from noisy observations. Examples show that the appropriate choice of sampling strategy can be of paramount importance in identification experiments. The design can be extended in a straightforward manner to safeguard against a single noninformative experiment in the case of diffuse prior distribution for the parameters.en_US
dc.languageengen_US
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/00207179.aspen_US
dc.relation.ispartofInternational Journal of Controlen_US
dc.titleON OPTIMAL CHOICE OF SAMPLING STRATEGIES FOR LINEAR SYSTEM IDENTIFICATION.en_US
dc.typeArticleen_US
dc.identifier.emailNg, Tung Sang:tsng@eee.hku.hken_US
dc.identifier.authorityNg, Tung Sang=rp00159en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-0016941404en_US
dc.identifier.volume23en_US
dc.identifier.issue4en_US
dc.identifier.spage459en_US
dc.identifier.epage475en_US
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridNg, Tung Sang=7402229975en_US
dc.identifier.scopusauthoridGoodwin, Graham Clifford=7201955514en_US

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