ON LINE IDENTIFICATION METHOD USING INSTRUMENTAL VARIABLES AND DECONVOLUTION.

Kollias, Stefanos; Halkias, Christos

dc.contributor.author	Kollias, Stefanos	en
dc.contributor.author	Halkias, Christos	en
dc.date.accessioned	2014-03-01T02:40:47Z
dc.date.available	2014-03-01T02:40:47Z
dc.date.issued	1984	en
dc.identifier.issn	01912216	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30228
dc.subject	arma model	en
dc.subject	Asymptotic Behaviour	en
dc.subject	Instrumental Variable	en
dc.subject	On-line Estimation	en
dc.subject	Parameter Estimation	en
dc.subject	Simulation Study	en
dc.subject	State Space Model	en
dc.subject.other	COMPUTER SYSTEMS, DIGITAL - On Line Operation	en
dc.subject.other	STATISTICAL METHODS - Regression Analysis	en
dc.subject.other	ARMA MODEL	en
dc.subject.other	DECONVOLUTION	en
dc.subject.other	INSTRUMENTAL VARIABLES	en
dc.subject.other	STATE SPACE MODEL	en
dc.subject.other	CONTROL SYSTEMS	en
dc.title	ON LINE IDENTIFICATION METHOD USING INSTRUMENTAL VARIABLES AND DECONVOLUTION.	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/CDC.1984.272410	en
heal.identifier.secondary	http://dx.doi.org/10.1109/CDC.1984.272410	en
heal.publicationDate	1984	en
heal.abstract	A method is proposed for the online estimation of the ARMA model parameters of a system whose input is white unmeasurable, stationary, or nonstationary noise. The method is based on the instrumental variable principle for recursive parameter estimation and on fixed-lag smoothing of the equivalent state-space model for deconvolution. The consistency and asymptotic behavior of this approach are discussed and a simulation study is given, which supports the theoretical results.	en
heal.publisher	IEEE, New York, NY, USA	en
heal.journalName	Proceedings of the IEEE Conference on Decision and Control	en
dc.identifier.doi	10.1109/CDC.1984.272410	en
dc.identifier.spage	429	en
dc.identifier.epage	434	en