Přístupnostní navigace
E-přihláška
Vyhledávání Vyhledat Zavřít
Detail publikace
DOKOUPIL, J. PAPEŽ, M. VÁCLAVEK, P.
Originální název
Bayesian comparison of Kalman filters with known covariance matrices
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
A growing-window recursive procedure for model comparison is proposed based on the Bayesian inference principle. This procedure, compared to the batch one, is capable of processing unlimited increases in 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 multiple Kalman filters. We investigate a case where the covariance of the measurement noise and the normalized covariance matrix of the process noise are both available.
Klíčová slova
Kalman filter, Bayesian methods, model comparison
Autoři
DOKOUPIL, J.; PAPEŽ, M.; VÁCLAVEK, P.
Rok RIV
2015
Vydáno
10. 3. 2015
ISBN
978-0-7354-1287-3
Kniha
AIP conference proceedings
ISSN
0094-243X
Periodikum
Ročník
1648
Stát
Spojené státy americké
Strany od
1
Strany do
4
Strany počet
URL
http://scitation.aip.org/content/aip/proceeding/aipcp/10.1063/1.4912383
BibTex
@inproceedings{BUT117758, author="Jakub {Dokoupil} and Milan {Papež} and Pavel {Václavek}", title="Bayesian comparison of Kalman filters with known covariance matrices", booktitle="AIP conference proceedings", year="2015", journal="AIP conference proceedings", volume="1648", pages="1--4", doi="10.1063/1.4912383", isbn="978-0-7354-1287-3", issn="0094-243X", url="http://scitation.aip.org/content/aip/proceeding/aipcp/10.1063/1.4912383" }