Global convergence of RTLSQEP: A solver of regularized total least squares problems via quadratic eigenproblems

Abstract

The total least squares (TLS) method is a successful approach for linear problems if both the matrix and the right hand side are contaminated by some noise. In a recent paper Sima, Van Huffel and Golub suggested an iterative method for solving regularized TLS problems, where in each iteration step a quadratic eigenproblem has to be solved. In this paper we prove its global convergence, and we present an efficient implementation using an iterative projection method with thick updates. First Published Online: 14 Oct 2010

Keywords

• total least squares method
• regularization
• quadratic eigenvalue problem