Taiwanese Journal of Mathematics


Jörg Lampe and Heinrich Voss

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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.

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

First available in Project Euclid: 18 July 2017

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Zentralblatt MATH identifier

Primary: 65F22: Ill-posedness, regularization

total least squares regularization ill-posedness nonlinear Arnoldi method


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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