Adaptive MV ARMA identification under the presence of noise

dc.contributor.author	Παππάς, Στυλιανός Σ.	el
dc.contributor.author	Μούσας, Βασίλειος Χ.	el
dc.contributor.author	Κατσικάς, Σωκράτης Κ.	el
dc.date.accessioned	2015-06-06T16:50:41Z
dc.date.available	2015-06-06T16:50:41Z
dc.date.issued	2015-06-06
dc.identifier.uri	http://hdl.handle.net/11400/15339
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://link.springer.com/chapter/10.1007%2F978-0-387-84814-3_17	el
dc.subject	Akaike's information criterions
dc.subject	Το κριτήριο του Akaike
dc.subject	ARMA model
dc.subject	Bayesian information criterion
dc.subject	Το κριτήριο του Bayesian
dc.subject	Order estimation
dc.subject	Εκτίμηση παραγγελίας
dc.title	Adaptive MV ARMA identification under the presence of noise	el
heal.type	conferenceItem
heal.classification	Engineering
heal.classification	Computer science
heal.classification	Μηχανική
heal.classification	Πληροφορική
heal.classificationURI	http://skos.um.es/unescothes/C01363
heal.classificationURI	http://skos.um.es/unescothes/C00750
heal.classificationURI	N/A-Μηχανική
heal.classificationURI	N/A-Πληροφορική
heal.keywordURI	http://zbw.eu/stw/descriptor/15327-0
heal.identifier.secondary	ISSN: 18761100
heal.identifier.secondary	ISBN: 978-038784813-6
heal.identifier.secondary	DOI: 10.1007/978-0-387-84814-3_17
heal.language	en
heal.access	campus
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Πολιτικών Μηχανικών Τ.Ε και Μηχανικών Τοπογραφίας & Γεωπληροφορικής Τ.Ε.	el
heal.publicationDate	2007-09
heal.bibliographicCitation	Pappas, S., Moussas, V. and Katsikas, S. (2007). Adaptive MV ARMA identification under the presence of noise. European Computing Conference. Athens, Greece. 25-27 September 2007. Available from: http://link.springer.com/chapter/10.1007%2F978-0-387-84814-3_17. [Accessed 25/03/2009]	en
heal.abstract	An adaptive method for simultaneous order estimation and parameter identification of multivariate (MV) ARMA models under the presence of noise is addressed. The proposed method is based on the well known multi-model partitioning (MMP) theory. Computer simulations indicate that the method is 100% successful in selecting the correct model order in very few steps. The results are compared with two other established order selection criteria, namely, Akaike's information criterion (AIC) and Schwarz's Bayesian information criterion (BIC).	en
heal.publisher	Springer Science+Business Media, LLC	en
heal.fullTextAvailability	true
heal.conferenceName	European Computing Conference	en
heal.conferenceItemType	full paper