A Hybrid Filtering Methodology for Nonlinear Estimation

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SYSNO ASEP	0351117
Document Type	A - Abstract
R&D Document Type	The record was not marked in the RIV
R&D Document Type	Není vybrán druh dokumentu
Title	A Hybrid Filtering Methodology for Nonlinear Estimation
Author(s)	Hofman, Radek (UTIA-B)_RID Dedecius, Kamil (UTIA-B)_{RID, ORCID}
Source Title	Abstracts of Contributions to 6th International Workshop on Data-Algorthms-Decision Making. - Praha : ÚTIA AV ČR, v.v.i, 2010 S. 46-46
Number of pages	1 s.
Action	6th International Workshop on Data-Algorithms-Decision Making
Event date	02.12.2010-04.12.2010
VEvent location	Jindrichuv Hradec
Country	CZ - Czech Republic
Language	eng - English
Country	CZ - Czech Republic
Keywords	hybrid filtering ; particle filter ; ensemble Kalman filter
Subject RIV	BC - Control Systems Theory
R&D Projects	1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
CEZ	AV0Z10750506 - UTIA-B (2005-2011)
Annotation	We are concerned with Bayesian estimation of a discrete stochastic process governed by a nonlinear model. We employ marginalized particle filter, which is also known as Rao-Blackwellised particle filter, for on-line tuning of nuisance parameters of analytical filters.
Workplace	Institute of Information Theory and Automation
Contact	Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
Year of Publishing	2011

Number of the records: 1