Comparing different types of approximators for choosing the parameters in the regularization of ill-posed problems

DOI10.1016/J.CAMWA.2003.02.015zbMath1069.65146OpenAlexW1996777637MaRDI QIDQ1779614

B. S. Bertram, John W. Hilgers

Publication date: 1 June 2005

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.camwa.2003.02.015

zbMATH Keywords

integral equationregularizationnumerical examplesill-posed problemsparameter choice

Mathematics Subject Classification ID

Numerical methods for integral equations (65R20) Numerical methods for ill-posed problems for integral equations (65R30) Fredholm integral equations (45B05)

Cites Work

• Choosing Regularization Parameters in Iterative Methods for Ill-Posed Problems
• Near-Optimal Parameters for Tikhonov and Other Regularization Methods
• A Trust-Region Approach to the Regularization of Large-Scale Discrete Forms of Ill-Posed Problems
• Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
• Erratum: On the Equivalence of Regularization and Certain Reproducing Kernel Hilbert Space Approaches for Solving First Kind Problems
• Fast CG-Based Methods for Tikhonov--Phillips Regularization
• The “Minimum Reconstruction Error” Choice of Regularization Parameters: Some More Efficient Methods and Their Application to Deconvolution Problems
• A General Heuristic for Choosing the Regularization Parameter in Ill-Posed Problems
• Fast Fourier-Hadamard decoding of orthogonal codes
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