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.
Citation
Jörg Lampe. Heinrich Voss. "SOLVING REGULARIZED TOTAL LEAST SQUARES PROBLEMS BASED ON EIGENPROBLEMS." Taiwanese J. Math. 14 (3A) 885 - 909, 2010. https://doi.org/10.11650/twjm/1500405873
Information