Optimal regularization for ill-posed problems in metric spaces
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Publication:5427263
DOI10.1515/JIIP.2007.007zbMath1132.65046OpenAlexW1997105661MaRDI QIDQ5427263
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Publication date: 19 November 2007
Published in: Journal of Inverse and Ill-posed Problems (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1515/jiip.2007.007
convergenceregularizationmetric spacesBanach spacelinear ill-posed problemsbalancing principleGaussian random noiseLepskij-type
Numerical solutions to equations with linear operators (65J10) Linear operators and ill-posed problems, regularization (47A52) Numerical solution to inverse problems in abstract spaces (65J22)
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Cites Work
- Regularization without preliminary knowledge of smoothness and error behaviour
- Nonlinear iterative methods for linear ill-posed problems in Banach spaces
- Practical Approximate Solutions to Linear Operator Equations When the Data are Noisy
- Geometry of linear ill-posed problems in variable Hilbert scales
- On a Problem of Adaptive Estimation in Gaussian White Noise
- Statistical Inverse Estimation in Hilbert Scales
- Analysis of the Recovery of Edges in Images and Signals by Minimizing Nonconvex Regularized Least-Squares
- Consistency and rates of convergence of nonlinear Tikhonov regularization with random noise
