DocumentCode
3537352
Title
Robust least-squares estimation with harmonic regressor: high order algorithms
Author
Stotsky, Alexander
Author_Institution
Signals & Syst., Chalmers Univ. of Technol., Gothenburg, Sweden
fYear
2013
fDate
10-13 Dec. 2013
Firstpage
6516
Lastpage
6521
Abstract
A new robust and computationally efficient solution to least-squares problem in the presence of round-off errors is proposed. The properties of a harmonic regressor are utilized for design of new combined algorithms of direct calculation of the parameter vector. In addition, an explicit transient bound for estimation error is derived for classical recursive least-squares (RLS) algorithm using Lyapunov function method. Different initialization techniques of the gain matrix are proposed as an extension of RLS algorithm. All the results are illustrated by simulations.
Keywords
Lyapunov methods; estimation theory; information theory; least squares approximations; regression analysis; Lyapunov function method; estimation error; explicit transient bound; gain matrix; harmonic regressor; high order algorithms; least-squares estimation; least-squares problem; parameter vector; recursive least-squares algorithm; Noise; Harmonic Regressor; High Order Algorithms; Recursive Inversion; Recursive Least-Squares Algorithm; Strictly Diagonally Dominant Matrix;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
Conference_Location
Firenze
ISSN
0743-1546
Print_ISBN
978-1-4673-5714-2
Type
conf
DOI
10.1109/CDC.2013.6760920
Filename
6760920
Link To Document