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Tikhonov Regularization and Total Least Squares by Gene H. Golub; Per Christian Hansen; Dianne P. O'Leary is a Computer Science article available to read on EtoBox.

What is Tikhonov Regularization and Total Least Squares about?

Discretizations of inverse problems lead to systems of linear equations with a highly ill-conditioned coefficient matrix, and in order to compute stable solutions to these systems it is necessary to apply regularization methods. We show how Tikhonov's regularization method, which in its original formulation involves a least squares problem, can be recast in a total least squares formulation suited for problems in which both the coefficient matrix and the right-hand side are known only approximately. We analyze the regularizing properties of this method and demonstrate by a numerical example that, in certain cases with large perturbations, the new method is superior to standard regularization methods.

Who reads Tikhonov Regularization and Total Least Squares?

Author

Gene H. Golub; Per Christian Hansen; Dianne P. O'Leary

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Published

1999

Language

EN

Field

Computer Science (Physical Sciences)