Recursive identification of the ARARX model based on the variational Bayes method
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F23%3APU149911" target="_blank" >RIV/00216305:26620/23:PU149911 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10383518" target="_blank" >https://ieeexplore.ieee.org/document/10383518</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CDC49753.2023.10383518" target="_blank" >10.1109/CDC49753.2023.10383518</a>
Alternative languages
Result language
angličtina
Original language name
Recursive identification of the ARARX model based on the variational Bayes method
Original language description
Bayesian parameter estimation of autoregressive (AR) with exogenous input (X) systems in the presence of colored model noise is addressed. The stochastic system under consideration is driven by colored noise that arises from passing an initially white noise through an AR filter. Owing to the additional AR filter, the ARARX schema provides more flexibility than the ARX one. The gained flexibility is countered by the fact that the ARARX system is no longer linear-in-parameters unless the white noise components or the AR noise filter are available. This paper analyzes the problem of estimating the unknown coefficients of the ARARX system and the model noise precision under conditions where the AR noise filter is both available and unavailable. While the former condition reduces the estimation problem to standard linear least squares, the latter one gives rise to an analytically intractable estimation problem. The intractability is resolved by the distributional approximation technique based on the variational Bayes (VB) method.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
62th IEEE Conference on Decision and Control
ISBN
979-8-3503-0124-3
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
4215-4222
Publisher name
IEEE
Place of publication
NEW YORK
Event location
Singapur
Event date
Dec 13, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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