A new heuristic parameter choice rule in Tikhonov regularization applied for Ritz approximation of an ill-posed problem
DOI10.4064/am2445-10-2021zbMath1480.65138OpenAlexW3216139256MaRDI QIDQ5031040
Publication date: 18 February 2022
Published in: Applicationes Mathematicae (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.4064/am2445-10-2021
Tikhonov regularizationill-posed problemsheuristic discrepancy principlenoise-level-free parameter choice rulesregularized Ritz approximation
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)
Uses Software
Cites Work
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- On the convergence of the quasioptimality criterion for (iterated) Tikhonov regularization
- Parameter determination for Tikhonov regularization problems in general form
- Convergence analysis of minimization-based noise level-free parameter choice rules for linear ill-posed problems
- Discretization independent convergence rates for noise level-free parameter choice rules for the regularization of ill-conditioned problems
- Regularization parameter determination for discrete ill-posed problems
- Semi-heuristic parameter choice rules for Tikhonov regularisation with operator perturbations
- Two-parameter discrepancy principle for combined projection and Tikhonov regularization of ill-posed problems
- On Minimization Strategies for Choice of the Regularization Parameter in Ill-Posed Problems
- The convergence of a new heuristic parameter selection criterion for general regularization methods
- Recent results on the quasi-optimality principle
- Remarks on choosing a regularization parameter using the quasi-optimality and ratio criterion
- Heuristic Parameter Choice in Tikhonov Method from Minimizers of the Quasi-Optimality Function
- The quasi-optimality criterion in the linear functional strategy
- A General Heuristic for Choosing the Regularization Parameter in Ill-Posed Problems
- DISCREPANCY SETS FOR COMBINED LEAST SQUARES PROJECTION AND TIKHONOV REGULARIZATION
- The approximate solution of Fredholm integral equations of the first kind
- Use of the regularization method in non-linear problems
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