On DREM regularization and unexcited linear ...
Type de document :
Communication dans un congrès avec actes
Titre :
On DREM regularization and unexcited linear regression estimation
Auteur(s) :
Aranovskiy, Stanislav [Auteur]
CentraleSupélec [campus de Rennes]
Institut d'Électronique et des Technologies du numéRique [IETR]
Ushirobira, Rosane [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
Efimov, Denis [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
CentraleSupélec [campus de Rennes]
Institut d'Électronique et des Technologies du numéRique [IETR]
Ushirobira, Rosane [Auteur]

Finite-time control and estimation for distributed systems [VALSE]
Efimov, Denis [Auteur]

Finite-time control and estimation for distributed systems [VALSE]
Titre de la manifestation scientifique :
62nd IEEE Conference on Decision and Control
Ville :
SINGAPORE
Pays :
Singapour
Date de début de la manifestation scientifique :
2023-12-13
Mot(s)-clé(s) en anglais :
DREM
Parameter Estimation
Excitation
Regularization
Parameter Estimation
Excitation
Regularization
Discipline(s) HAL :
Informatique [cs]/Systèmes et contrôle [cs.SY]
Sciences de l'ingénieur [physics]/Automatique / Robotique
Sciences de l'ingénieur [physics]/Automatique / Robotique
Résumé en anglais : [en]
The problem of estimation of unknown constant parameters in the linear regression with measurement noise is considered. Analysing different levels of excitation of the regressor, two notions of partial and feeble excitation ...
Lire la suite >The problem of estimation of unknown constant parameters in the linear regression with measurement noise is considered. Analysing different levels of excitation of the regressor, two notions of partial and feeble excitation are introduced. The former implies the absence of the persistent or interval excitation, while the latter property says that the excitation is just insufficient for an efficient estimation in a noisy setting. The dynamic extension and mixing method (DREM) is used for the problem solution, and in order to improve its estimation performance, regularization is proposed and the resulting improvement is investigated analytically. The theoretical findings are illustrated in the simulations.Lire moins >
Lire la suite >The problem of estimation of unknown constant parameters in the linear regression with measurement noise is considered. Analysing different levels of excitation of the regressor, two notions of partial and feeble excitation are introduced. The former implies the absence of the persistent or interval excitation, while the latter property says that the excitation is just insufficient for an efficient estimation in a noisy setting. The dynamic extension and mixing method (DREM) is used for the problem solution, and in order to improve its estimation performance, regularization is proposed and the resulting improvement is investigated analytically. The theoretical findings are illustrated in the simulations.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
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