A global minimization algorithm for Tikhonov functionals with sparsity constraints
DOI10.1080/00036811.2014.931025zbMath1311.65062arXiv1401.0435OpenAlexW2035061686WikidataQ58253937 ScholiaQ58253937MaRDI QIDQ4982032
Wei Wang, Bo Han, Ronny Ramlau, Stephan W. Anzengruber
Publication date: 23 March 2015
Published in: Applicable Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1401.0435
Variational inequalities (49J40) Nonlinear ill-posed problems (47J06) Numerical solutions to equations with nonlinear operators (65J15) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20) Linear operators and ill-posed problems, regularization (47A52) Numerical solution to inverse problems in abstract spaces (65J22)
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Cites Work
- Unnamed Item
- Nonlinear total variation based noise removal algorithms
- Regularization methods in Banach spaces.
- The global search in the Tikhonov scheme
- Convergence rates of a multilevel method for the regularization of nonlinear ill-posed problems
- Characteristic inequalities of uniformly convex and uniformly smooth Banach spaces
- Image recovery via total variation minimization and related problems
- A modified Landweber iteration for solving parameter estimation problems
- A Tikhonov-based projection iteration for nonlinear ill-posed problems with sparsity con\-straints
- Regularization properties of the sequential discrepancy principle for Tikhonov regularization in Banach spaces
- Convexity of the Tikhonov functional and iteratively regularized methods for solving irregular nonlinear operator equations
- Convergence rates for Morozov's discrepancy principle using variational inequalities
- Parameter choice in Banach space regularization under variational inequalities
- Convergence rates and source conditions for Tikhonov regularization with sparsity constraints
- Sparse regularization with l q penalty term
- Approximate source conditions for nonlinear ill-posed problems—chances and limitations
- On autoconvolution and regularization
- Analysis of bounded variation penalty methods for ill-posed problems
- TIGRA an iterative algorithm for regularizing nonlinear ill-posed problems
- A steepest descent algorithm for the global minimization of the Tikhonov functional
- An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
- Convergence rates of convex variational regularization
- A convergence rates result for Tikhonov regularization in Banach spaces with non-smooth operators
- Morozov's discrepancy principle for Tikhonov-type functionals with nonlinear operators
- Error estimates for non-quadratic regularization and the relation to enhancement
- Toward Global Convergence for Strongly Nonlinear Ill-Posed Problems via a Regularizing Multilevel Approach
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