Detail publikace
Kalman Filter and Identifiability of the Observation Model
BENKO, M. ŽÁK, L.
Anglický název
Kalman Filter and Identifiability of the Observation Model
Typ
Stať ve sborníku mimo WoS a Scopus
Jazyk
en
Originální abstrakt
Kalman filter has become a commonly used approach in many technological applications to filter uncertainty from noisy measurements. In this paper, we describe the Kalman filter as an optimal unbiased estimator of the hidden state in the linear model. Additionally, a discussion of the model estimation is provided. In the end, as an original contribution, a discussion of the observation model is done.
Klíčová slova anglicky
Hidden Markov model, Kalman filtering, Bayesian estimation, Parameter identifiability, Observation model
Vydáno
2024-10-24
Nakladatel
Statistical Society of Slovenia
Místo
Ljubljana, Slovenia
ISBN
978-961-94283-6-8
Kniha
23rd European Young Statisticians Meeting – Short of papers
Strany od–do
87–92
Počet stran
6
BIBTEX
@inproceedings{BUT200985,
author="Matej {Benko} and Libor {Žák}",
title="Kalman Filter and Identifiability of the Observation Model",
booktitle="23rd European Young Statisticians Meeting – Short of papers",
year="2024",
pages="87--92",
publisher="Statistical Society of Slovenia",
address="Ljubljana, Slovenia",
isbn="978-961-94283-6-8",
url="https://www.researchgate.net/profile/Andrej-Srakar/publication/397412266_23rd_European_Young_Statisticians_Meeting_11-15_September_2023_Ljubljana_Slovenia_Proceedings/links/690f2cf1a404d65709a419ee/23rd-European-Young-Statisticians-Meeting-11-15-September-2023-Ljubljana-Slovenia-Proceedings.pdf#page=101"
}