Detail publikace

Bayesian comparison of Kalman filters with known covariance matrices

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

AIP conference proceedings

Ročník

1648

Stát

Spojené státy americké

Strany od

1

Strany do

4

Strany počet

4

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"
}