Extrapolation of Tikhonov regularization method
Abstract
We consider regularization of linear ill‐posed problem Au = f with noisy data fδ, ¦fδ - f¦≤ δ . The approximate solution is computed as the extrapolated Tikhonov approximation, which is a linear combination of n ≥ 2 Tikhonov approximations with different parameters. If the solution u* belongs to R((A*A) n ), then the maximal guaranteed accuracy of Tikhonov approximation is O(δ 2/3) versus accuracy O(δ 2n/(2n+1)) of corresponding extrapolated approximation. We propose several rules for choice of the regularization parameter, some of these are also good in case of moderate over‐ and underestimation of the noise level. Numerical examples are given.
First published online: 09 Jun 2011
Keywords:
ill‐posed problems, regularization, Tikhonov method, extrapolation, noise level, regularization parameter choice, balancing principle, monotone error rule, rule R2How to Cite
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Copyright (c) 2010 The Author(s). Published by Vilnius Gediminas Technical University.
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Copyright (c) 2010 The Author(s). Published by Vilnius Gediminas Technical University.
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This work is licensed under a Creative Commons Attribution 4.0 International License.