Jörg Lampe, Heinrich Voss
The total least squares (TLS) method is a successful approach for linear problems when not only the right-hand side but the system matrix is also contaminated by some noise. For illposed TLS problems regularization is necessary to stabilize the computed solution. In this paper we present a new approach for computing an approximate solution of the Tikhonovregularized large-scale total least-squares problem. An iterative method is proposed which solves a convergent sequence of projected linear systems and thereby builds up a highly suitable search space. The focus is on efficient implementation with particular emphasis on the reuse of information.
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