Optimal Convergence Rates Results for Linear Inverse Problems in Hilbert Spaces
Date
2016
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Taylor & Francis
Abstract
In this article, we prove optimal convergence rates results for regularization methods for solving linear ill-posed operator equations in Hilbert spaces. The results generalizes existing convergence rates results on optimality to general source conditions, such as logarithmic source conditions. Moreover, we also provide optimality results under variational source conditions and show the connection to approximative source conditions.
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Albani, V., Elbau, P., de Hoop, M.V., et al.. "Optimal Convergence Rates Results for Linear Inverse Problems in Hilbert Spaces." Numerical Functional Analysis and Optimizationᅠ, 37, no. 5 (2016) Taylor & Francis: 521-540. http://dx.doi.org/10.1080/01630563.2016.1144070.
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This is an Open Access article. Non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly attributed, cited, and is not altered, transformed, or built upon in any way, is permitted. The moral rights of the named author(s) have been asserted.