Comparing some classes of bias-compensating least squares methods

Comparing some classes of bias-compensating least squares methods

Three different classes of bias-compensating least squares identification methods are compared, and shown to be identical. It is also discussed how the user parameters in the classes can be chosen to achieve optimal accuracy of the parameter estimates.

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Veröffentlicht in:Automatica (Oxford) 2013-03, Vol.49 (3), p.840-845
1. Verfasser: Soederstroem, Torsten
Format: Artikel
Sprache:eng
Schlagworte:
Applied sciences
Automation
Bias compensation
Computer science
control theory
systems
Control theory. Systems
Errors-in-variables models
Estimates
Exact sciences and technology
Identification methods
Least squares method
Linear systems
Modelling and identification
Optimization
System identification
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Beschreibung
Zusammenfassung:Three different classes of bias-compensating least squares identification methods are compared, and shown to be identical. It is also discussed how the user parameters in the classes can be chosen to achieve optimal accuracy of the parameter estimates.
ISSN:0005-1098
1873-2836
1873-2836
DOI:10.1016/j.automatica.2013.01.003