Comparisons of parameter choice methods for regularization with discrete noisy data

DOI10.1088/0266-5611/14/1/014zbMath0904.65053OpenAlexW2074701756MaRDI QIDQ4381828

Mark A. Lukas

Publication date: 19 January 1999

Published in: Inverse Problems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1088/0266-5611/14/1/014

zbMATH Keywords

Sobolev spacenumerical examplesHilbert spaceasymptotic stabilitydiscrepancy principlelinear ill-posed problemsgeneralized cross-validationmethod of regularizationlinear ill-posed operator equationfirst-kind integral equationdiscrete, noisy dataminimum bound methodunbiased error methodunbiased risk method

Mathematics Subject Classification ID

Numerical methods for integral equations (65R20) Numerical solutions to equations with linear operators (65J10) Equations and inequalities involving linear operators, with vector unknowns (47A50) Numerical methods for ill-posed problems for integral equations (65R30) Fredholm integral equations (45B05) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20)

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