Detail publikačního výsledku

Variable exponential forgetting for estimation of the statistics of the normal-Wishart distribution with a constant precision

DOKOUPIL, J.; VÁCLAVEK, P.

Originální název

Variable exponential forgetting for estimation of the statistics of the normal-Wishart distribution with a constant precision

Anglický název

Variable exponential forgetting for estimation of the statistics of the normal-Wishart distribution with a constant precision

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

The problem of estimating normal regression-type models with possibly time-varying regression parameters and constant noise precision is considered and examined from the Bayesian viewpoint. The solution we propose exploits a collaborative decision in order to face the incomplete model of parameter variations. Under this approach, a loss functional evaluating two prediction alternatives is constructed, which allows us to merge both alternatives, complying with the principles of optimization theory. Specifically, the posterior probability density function (pdf) and its flattened variant are combined by means of the geometric mean with automatically adjusted weights. The result is an automatic rescaling of the covariance matrix through the forgetting factor in response to empirically confirmed performance.

Anglický abstrakt

The problem of estimating normal regression-type models with possibly time-varying regression parameters and constant noise precision is considered and examined from the Bayesian viewpoint. The solution we propose exploits a collaborative decision in order to face the incomplete model of parameter variations. Under this approach, a loss functional evaluating two prediction alternatives is constructed, which allows us to merge both alternatives, complying with the principles of optimization theory. Specifically, the posterior probability density function (pdf) and its flattened variant are combined by means of the geometric mean with automatically adjusted weights. The result is an automatic rescaling of the covariance matrix through the forgetting factor in response to empirically confirmed performance.

Klíčová slova

forgetting factor; Kullback-Leibler divergence; normal-Wishart distribution

Klíčová slova v angličtině

forgetting factor; Kullback-Leibler divergence; normal-Wishart distribution

Autoři

DOKOUPIL, J.; VÁCLAVEK, P.

Rok RIV

2020

Vydáno

11.12.2019

Nakladatel

IEEE

Místo

Nice, France

ISBN

978-1-7281-1397-5

Kniha

58th Conference on Decision and Control

Strany od

5094

Strany do

5100

Strany počet

7

BibTex

@inproceedings{BUT160943,
  author="Jakub {Dokoupil} and Pavel {Václavek}",
  title="Variable exponential forgetting for estimation of the statistics of the normal-Wishart distribution with a constant precision",
  booktitle="58th Conference on Decision and Control",
  year="2019",
  pages="5094--5100",
  publisher="IEEE",
  address="Nice, France",
  doi="10.1109/CDC40024.2019.9029290",
  isbn="978-1-7281-1397-5"
}