Recursive Variational Inference for Total Least-Squares

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F23%3APU148748" target="_blank" >RIV/00216305:26620/23:PU148748 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10163935" target="_blank" >https://ieeexplore.ieee.org/document/10163935</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/LCSYS.2023.3289608" target="_blank" >10.1109/LCSYS.2023.3289608</a>

Result language
angličtina
Original language name
Recursive Variational Inference for Total Least-Squares
Original language description
This letter analyzes methods for deriving credible intervals to facilitate errors-in-variables identification by expanding on Bayesian total least squares. The credible intervals are approximated employing Laplace and variational approximations of the intractable posterior density function. Three recursive identification algorithms providing an approximation of the credible intervals for inference with the Bingham and the Gaussian priors are proposed. The introduced algorithms are evaluated on numerical experiments, and a practical example of application on battery cell total capacity estimation compared to the state-of-the-art algorithms is presented.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20200 - Electrical engineering, Electronic engineering, Information engineering

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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