Taiwanese Journal of Mathematics

SOLVING REGULARIZED TOTAL LEAST SQUARES PROBLEMS BASED ON EIGENPROBLEMS

Jörg Lampe and Heinrich Voss

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Abstract

The total least squares (TLS) method is a successful approach for linear problems if both the system matrix and the right hand side are contaminated by some noise. For ill-posed TLS problems regularization is necessary to stabilize the computed solution. In this paper we summarize two iterative methods which are based on a sequence of eigenproblems. The focus is on efficient implementation with particular emphasis on the reuse of information gained during the convergence history.

Article information

Source
Taiwanese J. Math., Volume 14, Number 3A (2010), 885-909.

Dates
First available in Project Euclid: 18 July 2017

Permanent link to this document
https://projecteuclid.org/euclid.twjm/1500405873

Digital Object Identifier
doi:10.11650/twjm/1500405873

Mathematical Reviews number (MathSciNet)
MR2667723

Zentralblatt MATH identifier
1198.65081

Subjects
Primary: 65F22: Ill-posedness, regularization

Keywords
total least squares regularization ill-posedness nonlinear Arnoldi method

Citation

Lampe, Jörg; Voss, Heinrich. SOLVING REGULARIZED TOTAL LEAST SQUARES PROBLEMS BASED ON EIGENPROBLEMS. Taiwanese J. Math. 14 (2010), no. 3A, 885--909. doi:10.11650/twjm/1500405873. https://projecteuclid.org/euclid.twjm/1500405873


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