Data-driven stabilized forgetting design using the geometric mean of normal probability densities
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F18%3APU130162" target="_blank" >RIV/00216305:26620/18:PU130162 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8619117" target="_blank" >https://ieeexplore.ieee.org/document/8619117</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CDC.2018.8619117" target="_blank" >10.1109/CDC.2018.8619117</a>
Alternative languages
Result language
angličtina
Original language name
Data-driven stabilized forgetting design using the geometric mean of normal probability densities
Original language description
This paper contributes to the solution of adaptive tracking issues adopting Bayesian principles. The incomplete model of parameter variations is substituted by relaying on the use of data-suppressing procedure with two goals pursued: to provide automatic memory scheduling through the data-driven forgetting factor, and to compensate for the potential loss of persistency. The solution we propose is the geometric mean of the posterior probability density function (pdf) and its proper alternative, which, for the normal distribution, can be reduced to the convex combination of the information matrix and its regular counterpart. This coupling policy results from maximin decision-making, where the Kullback-Leibler divergence (KLD) occurs as a measure of discrepancy. In this context, the weight (probability) assigned to the information matrix is regarded as the forgetting factor and is controlled by a globally convergent Newton algorithm.
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
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
57th Conference on Decision and Control
ISBN
978-1-5386-1394-8
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
1403-1408
Publisher name
IEEE
Place of publication
neuveden
Event location
Miami Beach, Florida, USA
Event date
Dec 17, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000458114801055