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Detail publikačního výsledku
LEBEDA, A.
Originální název
Estimation of parameters of one-step predictor with particle filter method
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
This paper is focused on estimation of the parameters of a system with non-Gaussian noise. Firstly, the Bayesian inference is described and the method of the particle filters is introduced which is directly based on the Bayesian inference. The particle filters method numrically solve a problem of a recursive Bayesian state estimator. Secondly, the method for transformation of a random variables is introduced which changes the relative likelihood of the particle filters according to the distribution of the measurement noise. Thirdly, recursive least square method is derived and linear one-step predictor is described. Fourthly, parameters of the one-step predictor are estimated online with two methods that were mention before. The outputs of both methods are compared and results are discussed. The particle filters method with random variables is analyzed.
Anglický abstrakt
Klíčová slova
particle filters, non-Gaussian, Bayessian inference, identification, linear model
Klíčová slova v angličtině
částicové filtry, neGausovské systémy, Bayesovská inference, identifikace, lineární model
Autoři
Rok RIV
2016
Vydáno
13.05.2015
Nakladatel
Silesian University of Technology, Poland
Místo
Cracow, Poland
Kniha
13th IFAC Conference on Programmable Devices and Embedded Systems - PDeS 2015
ISSN
1474-6670
Periodikum
Programmable devices and systems
Svazek
2015
Číslo
13
Stát
Spojené království Velké Británie a Severního Irska
Strany od
256
Strany do
261
Strany počet
6
URL
https://www.sciencedirect.com/science/article/pii/S2405896315008186
BibTex
@inproceedings{BUT115314, author="Aleš {Lebeda}", title="Estimation of parameters of one-step predictor with particle filter method", booktitle="13th IFAC Conference on Programmable Devices and Embedded Systems - PDeS 2015", year="2015", journal="Programmable devices and systems", volume="2015", number="13", pages="256--261", publisher="Silesian University of Technology, Poland", address="Cracow, Poland", doi="10.1016/j.ifacol.2015.07.043", issn="1474-6670", url="https://www.sciencedirect.com/science/article/pii/S2405896315008186" }