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DOKOUPIL, J. PAPEŽ, M. VÁCLAVEK, P.
Originální název
Comparison of Kalman filters formulated as the statistics of the Normal-inverse-Wishart distribution
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
A novel growing-window recursive procedure for Kalman filter comparison is proposed based on the Bayesian inference principle. This procedure is capable of processing unlimited growth of the uncertainty of the initial parameter settings, which is a characteristic of Kalman type algorithms. The present paper applies the suggested procedure to assess the degree of support for the state point estimates generated by Kalman filters differing in their system model descriptions. The algebraic form of the comparison algorithm covers the situation when the covariance of the measurement noise is known as well as is unknown and the normalized covariance matrix of the process noise is always available. In this respect, the Kalman filter is formulated here as recursive learning of the sufficient statistics of the Normal and Normal-inverse-Wishart distributions.
Klíčová slova
Kalman filter, Bayesian methods, model comparison
Autoři
DOKOUPIL, J.; PAPEŽ, M.; VÁCLAVEK, P.
Rok RIV
2015
Vydáno
15. 12. 2015
Nakladatel
Institute of electrical and electronics engineers inc.
ISBN
978-1-4799-7884-7
Kniha
54th IEEE Conference on Decision and Control
ISSN
0743-1546
Periodikum
Stát
Spojené státy americké
Strany od
5008
Strany do
5013
Strany počet
6
URL
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7403002
BibTex
@inproceedings{BUT119580, author="Jakub {Dokoupil} and Milan {Papež} and Pavel {Václavek}", title="Comparison of Kalman filters formulated as the statistics of the Normal-inverse-Wishart distribution", booktitle="54th IEEE Conference on Decision and Control", year="2015", journal="54th IEEE Conference on Decision and Control", pages="5008--5013", publisher="Institute of electrical and electronics engineers inc.", doi="10.1109/CDC.2015.7403002", isbn="978-1-4799-7884-7", issn="0743-1546", url="http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7403002" }