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Displaying similar documents to “Some insights into the regularization of ill-posed problems.”

Residual norm behavior for Hybrid LSQR regularization

Havelková, Eva, Hnětynková, Iveta

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Hybrid LSQR represents a powerful method for regularization of large-scale discrete inverse problems, where ill-conditioning of the model matrix and ill-posedness of the problem make the solutions seriously sensitive to the unknown noise in the data. Hybrid LSQR combines the iterative Golub-Kahan bidiagonalization with the Tikhonov regularization of the projected problem. While the behavior of the residual norm for the pure LSQR is well understood and can be used to construct a stopping...