bibtype	C - Conference Paper (international conference)
ARLID	0085041
utime	20240103184350.0
mtime	20070829235959.9
title (primary) (eng)	Initial Conditions for Kalman Filtering: Prior Knowledge Specification
specification	page_count 5 s. media_type CD ROM
serial	ARLID cav_un_epca*0085040 ISBN 978-960-8457-98-0 title Proceedings of the 7th WSEAS International Conference on Systems Theory and Scientific Computation (ISTASC'07) page_num 45-49 publisher place Athens name WSEAS Press year 2007 editor name1 Le name2 Minh Hung editor name1 Demiralp name2 Metin editor name1 Mladenov name2 Valeri editor name1 Bojkovic name2 Zoran
title (cze)	Počáteční podmínky pro Kalmanův filtr: specifkace apriorní znalosti
keyword	Kalman filtering
keyword	prior knowledge
keyword	state-space model
keyword	exponential family
author (primary)	ARLID cav_un_auth*0108105 name1 Suzdaleva name2 Evgenia institution UTIA-B full_dept Department of Signal Processing fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source	url http://as.utia.cz/publications/2007/Suz_07.pdf
cas_special	project project_id 1ET100750401 agency GA AV ČR ARLID cav_un_auth*0001792 project project_id 1F43A/003/120 agency GA MDS ARLID cav_un_auth*0001975 project project_id GP201/06/P434 agency GA ČR country CZ ARLID cav_un_auth*0215307 research CEZ:AV0Z10750506 abstract (eng) The paper deals with a selection of the initial state for Kalman filtering. In practice the initial state mean and covariance are often chosen arbitrarily. The present paper considers the problem from the position of knowledge elicitation and proposes a methodology to extract the prior knowledge from available information by the respective processing in order to choose the adequate initial conditions. The suggested methodology is based on utilization of the conjugate prior distribution for models, belonging to the exponential family. abstract (cze) Článek se zabývá problémem výběru počátečního stavu pro Kalmanův filtr. Střední hodnota a kovarianční matice počátečního stavu nebývají v praxi často voleny metodicky. V článku je navržena metodologie extrakce apriorní znalosti z dostupné expertní informace pro výběr počátečních podmínek. Navržená metodologie je založena na využití sdružené apriorní hustoty modelů patřících do exponenciální rodiny. action ARLID cav_un_auth*0229575 name 7th WSEAS International Conference on Systems Theory and Scientific Computation (ISTASC'07) place Athens dates 24.08.2007-26.08.2007 country GR reportyear 2008 RIV BB permalink http://hdl.handle.net/11104/0147633 arlyear 2007 mrcbU63 cav_un_epca*0085040 Proceedings of the 7th WSEAS International Conference on Systems Theory and Scientific Computation (ISTASC'07) 978-960-8457-98-0 45 49 Athens WSEAS Press 2007 mrcbU67 Le Minh Hung 340 mrcbU67 Demiralp Metin 340 mrcbU67 Mladenov Valeri 340 mrcbU67 Bojkovic Zoran 340