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Global convergence of RTLSQEP : a solver of regularized total least squares problems via quadratic eigenproblems
Citation Link: https://doi.org/10.15480/882.2328
Publikationstyp
Journal Article
Date Issued
2008-02-15
Sprache
English
Author(s)
Voß, Heinrich
TORE-DOI
TORE-URI
Volume
13
Issue
1
Start Page
55
End Page
66
Citation
Mathematical Modelling and Analysis 1 (13): 55-66 (2008)
Publisher DOI
Scopus ID
Publisher
Vilnius Gediminas Technical University
The total least squares (TLS) method is a successful approach for linear problems if both the matrix and the right hand side are contaminated by some noise. In a recent paper Sima, Van Huffel and Golub suggested an iterative method for solving regularized TLS problems, where in each iteration step a quadratic eigenproblem has to be solved. In this paper we prove its global convergence, and we present an efficient implementation using an iterative projection method with thick updates.
Subjects
total least squares method
regularization
quadratic eigenvalue problem
DDC Class
510: Mathematik
More Funding Information
Bundesministerium für Bildung und Forschung, BMBF
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