Optimal decentralized Kalman filter and Lainiotis filter

dc.contributor.author	Ασημάκης, Νικόλαος Δ.	el
dc.contributor.author	Αδάμ, Μαρία	el
dc.contributor.author	Κοζύρη, Μαρία	el
dc.contributor.author	Βολιώτης, Σταμάτης Δ.	el
dc.contributor.author	Ασημάκης, Κωνσταντίνος	el
dc.date.accessioned	2015-05-21T10:18:41Z
dc.date.available	2015-05-21T10:18:41Z
dc.date.issued	2015-05-21
dc.identifier.uri	http://hdl.handle.net/11400/10827
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://www.sciencedirect.com/science/article/pii/S1051200412001741#	el
dc.subject	Discrete-time systems
dc.subject	Optimization
dc.subject	Kalman filter
dc.subject	Φίλτρο Kalman
dc.subject	Lainiotis filter
dc.subject	Φίλτρο Λαϊνιώτης
dc.subject	Συστήματα διακριτού χρόνου
dc.subject	Decentralized algorithms
dc.subject	Αποκεντρωμένοι αλγόριθμοι
dc.subject	Analysis of algorithms
dc.subject	Ανάλυση αλγορίθμων
dc.subject	Βελτιστοποίηση
dc.title	Optimal decentralized Kalman filter and Lainiotis filter	en
heal.type	journalArticle
heal.classification	Technology
heal.classification	Electrical engineering
heal.classification	Τεχνολογία
heal.classification	Ηλεκτρολογία Μηχανολογία
heal.classificationURI	http://zbw.eu/stw/descriptor/10470-6
heal.classificationURI	http://skos.um.es/unescothes/C01311
heal.classificationURI	N/A-Τεχνολογία
heal.classificationURI	N/A-Ηλεκτρολογία Μηχανολογία
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh85038370
heal.keywordURI	http://skos.um.es/unescothes/C02848
heal.identifier.secondary	doi:10.1016/j.dsp.2012.08.005
heal.language	en
heal.access	free
heal.publicationDate	2013-01
heal.bibliographicCitation	Assimakis, N., Adam, M., Koziri, M., Voliotis, S. and Asimakis, K. (2013). Optimal decentralized Kalman filter and Lainiotis filter. "Digital Signal Processing", 23(1), January 2013. pp. 442–452. Available from: http://www.sciencedirect.com/science/article/pii/S1051200412001741#. [Accessed 16/08/2012]	en
heal.abstract	A method to implement the optimal decentralized Kalman filter and the optimal decentralized Lainiotis filter is proposed; the method is based on the a priori determination of the optimal distribution of measurements into parallel processors, minimizing the computation time. The resulting optimal Kalman filter and optimal Lainiotis filter require uniform distribution or near to uniform distribution of measurements into parallel processors. The optimal uniform distribution has the advantages of elimination of idle time for the local processors and of low hardware cost, but it is not always applicable. The optimal filters present high parallelism speedup; this is verified through simulation results and is very important due to the fact that, in most real-time applications, it is essential to obtain the estimate in the shortest possible time.	en
heal.journalName	Digital Signal Processing	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true