Improvement of the density fitting approach for the Gaussian electrostatic model via the use of the discrete Picard condition in Tychonov regularization. [PDF]
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Exploiting Residual Information in the Parameter Choice for Discrete Ill-Posed Problems
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Improved Microwave Imaging with the Extended Born Iterative Method. [PDF]
IEEE Trans Antennas PropagIslam MS, Islam A, Kiourti A.
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Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery. [PDF]
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Old and new parameter choice rules for discrete ill-posed problems
Numerical Algorithms, 2013 L. Reichel, G. Rodriguez
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Combining approximate solutions for linear discrete ill-posed problems
, 2011 Linear discrete ill-posed problems of small to medium size are commonly solved by first computing the singular value decomposition of the matrix and then determining an approximate solution by one of several available numerical methods, such as the truncated singular value decomposition or Tikhonov regularization.
Hochstenbach, M.E., Reichel, L.
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An Efficient Algorithm for Spatial-Spectral Partial Volume Compartment Mapping with Applications to Multicomponent Diffusion and Relaxation MRI. [PDF]
IEEE Trans Comput ImagingLiu Y +4 more
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An $$\ell ^2-\ell ^q$$ℓ2-ℓq Regularization Method for Large Discrete Ill-Posed Problems
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A locally adaptive regularization of a hybrid variational model for color image diffusion via integration of diffusion with normalized data. [PDF]
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Learning a Filtered Backprojection Reconstruction Method for Photoacoustic Computed Tomography With Hemispherical Measurement Geometries. [PDF]
IEEE Trans Med ImagingChen P +6 more
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