Compact discrepancy and chi-squared principles for over-determined inverse problems

DOI10.1515/jiip-2015-0040zbMath1368.65064OpenAlexW2519090839MaRDI QIDQ2397874

Publication date: 24 May 2017

Published in: Journal of Inverse and Ill-Posed Problems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/jiip-2015-0040

zbMATH Keywords

regularization singular value decomposition compact discrepancy principle chi-squared principle over-determined truncated cost function variance suppression

Mathematics Subject Classification ID

Numerical solutions to overdetermined systems, pseudoinverses (65F20) Ill-posedness and regularization problems in numerical linear algebra (65F22)

Uses Software

Regularization tools
UTV

Cites Work

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Comparing parameter choice methods for regularization of ill-posed problems
The truncated SVD as a method for regularization
A posteriori parameter choice for general regularization methods for solving linear ill-posed problems
Regularization parameter estimation for large-scale Tikhonov regularization using a priori information
Regularization tools version \(4.0\) for matlab \(7.3\)
Exploiting residual information in the parameter choice for discrete ill-posed problems
On the choice of the regularization parameter in ill-posed problems with approximately given noise level of data
Residual periodograms for choosing regularization parameters for ill-posed problems
A priori weighting for parameter estimation
A Newton root-finding algorithm for estimating the regularization parameter for solving ill-conditioned least squares problems
A Technique for the Numerical Solution of Certain Integral Equations of the First Kind
Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
Algorithms for the regularization of ill-conditioned least squares problems
Practical Approximate Solutions to Linear Operator Equations When the Data are Noisy
The Use of the L-Curve in the Regularization of Discrete Ill-Posed Problems
Rank-Deficient and Discrete Ill-Posed Problems
Test Matrices for Regularization Methods
Computational Methods for Inverse Problems
A Regularization Parameter in Discrete Ill-Posed Problems
Some Comments on C P

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