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Optimal regularization for ill-posed problems in metric spaces
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F. Bauer
Published/Copyright:
May 25, 2007
We present a strategy for choosing the regularization parameter (Lepskij-type balancing principle) for ill-posed problems in metric spaces with deterministic or stochastic noise. Additionally we improve the strategy in comparison to the previously used version for Hilbert spaces in some ways.
Published Online: 2007-05-25
Published in Print: 2007-05-23
Copyright 2007, Walter de Gruyter
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Keywords for this article
Regularization in normed spaces,;
Lepskij-type balancing principle,;
-spaces.
Articles in the same Issue
- Parameter estimation versus homogenization techniques in time-domain characterization of composite dielectrics
- Optimal regularization for ill-posed problems in metric spaces
- A dual algorithm for denoising and preserving edges in image processing
- A globally convergent convexification algorithm for multidimensional coefficient inverse problems
- Numerical solution of inverse heat conduction problems in two spatial dimensions
- Imaging low sensitivity regions in petroleum reservoirs using topological perturbations and level sets
