Adaptive strategy for the damping parameters in an iteratively regularized Gauss-Newton method

DOI10.1023/A:1021773116353zbMath0933.65062OpenAlexW1935847497MaRDI QIDQ1281969

Otmar Scherzer, Mårten Gulliksson

Publication date: 13 September 1999

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1023/a:1021773116353

zbMATH Keywords

performancediscrepancy principleregularization methodnonlinear ill-posed problemsGauss-Newton methodnonlinear least square problemsdamping parameter choice

Mathematics Subject Classification ID

Iterative procedures involving nonlinear operators (47J25) Numerical solutions to equations with nonlinear operators (65J15) Complexity and performance of numerical algorithms (65Y20) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20)

Cites Work

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• Convergence of Newton-like methods for singular operator equations using outer inverses
• A modified Landweber iteration for solving parameter estimation problems
• A convergence analysis of the Landweber iteration for nonlinear ill-posed problems
• Finite-dimensional approximation of tikhonov regularized solutions of non-linear ill-posed problems
• Convergence rates for Tikhonov regularisation of non-linear ill-posed problems
• On convergence rates for the iteratively regularized Gauss-newton method
• Rank-Deficient and Discrete Ill-Posed Problems
• Regularizing properties of a truncated newton-cg algorithm for nonlinear inverse problems

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