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 :
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