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ASU Scholarship Showcase

This growing collection, which contains many open access articles, consists of scholarly works authored by ASU community members. ASU-affiliated authors, who wish to deposit scholarly works, please use the Deposit form to describe your work.

Tikhonov regularization for projected solutions of large-scale ill-posed problems is considered. The Golub{Kahan iterative bidiagonalization is used to project the problem onto a subspace and regularization then applied to nd a subspace approximation to the full problem. Determination of the regularization, parameter for the projected problem by unbiased predictive risk estimation, generalized cross validation, and discrepancy principle techniques is investigated. It is shown that the regularized parameter obtained by the unbiased predictive risk estimator can provide a good estimate which can be used for a full problem that is moderately to severely ill-posed. A similar analysis provides the weight parameter ...

Renaut, Rosemary
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