Detail publikace

Recursive Variational Inference for Total Least-Squares

FRIML, D. VÁCLAVEK, P.

Originální název

Recursive Variational Inference for Total Least-Squares

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Bayes methods; parameter estimation; identification; variational methods

Autoři

FRIML, D.; VÁCLAVEK, P.

Vydáno

26. 6. 2023

Nakladatel

IEEE

Místo

PISCATAWAY

ISSN

2475-1456

Periodikum

IEEE Control Systems Letters

Ročník

7

Číslo

1

Stát

Spojené státy americké

Strany od

2839

Strany do

2844

Strany počet

6

URL

https://ieeexplore.ieee.org/document/10163935

Plný text v Digitální knihovně

http://hdl.handle.net/11012/244278

BibTex

@article{BUT184309,
  author="Dominik {Friml} and Pavel {Václavek}",
  title="Recursive Variational Inference for Total Least-Squares",
  journal="IEEE Control Systems Letters",
  year="2023",
  volume="7",
  number="1",
  pages="2839--2844",
  doi="10.1109/LCSYS.2023.3289608",
  issn="2475-1456",
  url="https://ieeexplore.ieee.org/document/10163935"
}