Smoothing and regularization with modified sparse approximate inverses

DOI10.1155/2010/930218zbMath1229.65058OpenAlexW2054744919WikidataQ58652014 ScholiaQ58652014MaRDI QIDQ543017

Thomas Kilian Huckle, Matous Sedlacek

Publication date: 20 June 2011

Published in: Journal of Electrical and Computer Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2010/930218

Mathematics Subject Classification ID

Iterative numerical methods for linear systems (65F10) Numerical computation of matrix norms, conditioning, scaling (65F35) Parallel numerical computation (65Y05) Preconditioners for iterative methods (65F08)

Related Items

A hybrid recursive multilevel incomplete factorization preconditioner for solving general linear systems ⋮ Sparse matrix approximations for multigrid methods ⋮ Image deblurring by sparsity constraint on the Fourier coefficients ⋮ Data based regularization for discrete deconvolution problems ⋮ On finding robust approximate inverses for large sparse matrices

Uses Software

• Regularization tools
• RestoreTools
• MSPAI

Cites Work

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• A comparative study of sparse approximate inverse preconditioners
• Regularization tools: A Matlab package for analysis and solution of discrete ill-posed problems
• Iterative methods for image deblurring: A Matlab object-oriented approach
• Robust Parallel Smoothing for Multigrid Via Sparse Approximate Inverses
• The Interface Probing Technique in Domain Decomposition
• Approximate inverse preconditionings for sparse linear systems
• Analysis of Discrete Ill-Posed Problems by Means of the L-Curve
• Iterative Solution Methods
• Parallel Preconditioning with Sparse Approximate Inverses
• Restoring Images Degraded by Spatially Variant Blur
• Sparse Approximate Inverse Smoother for Multigrid
• Sparse Approximate Inverses and Target Matrices
• Compact Fourier Analysis for Designing Multigrid Methods
• Frobenius norm minimization and probing for preconditioning

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