Enregistré dans:
Détails bibliographiques
Auteurs principaux: Ortega, Romeo, Romero, Jose Guadalupe, Aranovskiy, Stanislav, Tao, Gang
Format: Preprint
Publié: 2025
Sujets:
Accès en ligne:https://arxiv.org/abs/2506.08211
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866913887155126272
author Ortega, Romeo
Romero, Jose Guadalupe
Aranovskiy, Stanislav
Tao, Gang
author_facet Ortega, Romeo
Romero, Jose Guadalupe
Aranovskiy, Stanislav
Tao, Gang
contents In this brief note we recall the little-known fact that, for linear regression equations (LRE) with intervally excited (IE) regressors, standard Least Square (LS) parameter estimators ensure finite convergence time (FCT) of the estimated parameters. The convergence time being equal to the time length needed to comply with the IE assumption. As is well-known, IE is necessary and sufficient for the identifiability of the LRE-hence, it is the weakest assumption for the on-or off-line solution of the parameter estimation problem.
format Preprint
id arxiv_https___arxiv_org_abs_2506_08211
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Standard LSParameter Estimators Ensure Finite Convergence Time for Linear Regression Equations Under an Interval Excitation Assumption
Ortega, Romeo
Romero, Jose Guadalupe
Aranovskiy, Stanislav
Tao, Gang
Systems and Control
Statistics Theory
In this brief note we recall the little-known fact that, for linear regression equations (LRE) with intervally excited (IE) regressors, standard Least Square (LS) parameter estimators ensure finite convergence time (FCT) of the estimated parameters. The convergence time being equal to the time length needed to comply with the IE assumption. As is well-known, IE is necessary and sufficient for the identifiability of the LRE-hence, it is the weakest assumption for the on-or off-line solution of the parameter estimation problem.
title Standard LSParameter Estimators Ensure Finite Convergence Time for Linear Regression Equations Under an Interval Excitation Assumption
topic Systems and Control
Statistics Theory
url https://arxiv.org/abs/2506.08211