Title
On Weakly Bounded Noise In Ill-Posed Problems
Abstract
We study compact operator equations with noisy data in Hilbert space. Instead of assuming that the error in the data converges strongly to zero, we only assume a type of weak convergence. Under the source conditions that are usually assumed in the presence of convex constraints, we derive optimal convergence rates for convexly constrained Phillips-Tikhonov regularization. We also discuss a version of the Lepskii method for selecting the regularization parameter. © 2009 IOP Publishing Ltd.
Publication Date
11-26-2009
Publication Title
Inverse Problems
Volume
25
Issue
11
Number of Pages
-
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1088/0266-5611/25/11/115018
Copyright Status
Unknown
Socpus ID
70450202718 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/70450202718
STARS Citation
Eggermont, P. P.B.; Lariccia, V. N.; and Nashed, M. Z., "On Weakly Bounded Noise In Ill-Posed Problems" (2009). Scopus Export 2000s. 11128.
https://stars.library.ucf.edu/scopus2000/11128