Article ID Journal Published Year Pages File Type
418103 Computational Statistics & Data Analysis 2007 13 Pages PDF
Abstract

A computational approach for solving regularized total least squares problems via a sequence of quadratic eigenvalue problems has recently been proposed. Taking advantage of a variational characterization of real eigenvalues of nonlinear eigenproblems the existence of a real right-most eigenvalue for each quadratic eigenvalue problem in the sequence is proven. For large problems the approach is improved considerably utilizing information from the previous quadratic problems and early updates in a nonlinear Arnoldi method.

Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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