Abstract
Abstract
In this paper, we consider linear ill-posed problems in Hilbert spaces and their regularization via frame decompositions, which are generalizations of the singular-value decomposition. In particular, we prove convergence for a general class of continuous regularization methods and derive convergence rates under both a priori and a posteriori parameter choice rules. Furthermore, we apply our derived results to a standard tomography problem based on the Radon transform.
Funder
Upper Austrian Government
Austrian Science Fund
Subject
Applied Mathematics,Computer Science Applications,Mathematical Physics,Signal Processing,Theoretical Computer Science
Cited by
6 articles.
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