Results 161 to 170 of about 21,724 (205)
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Fractional Tikhonov regularization method in Hilbert scales

Applied Mathematics and Computation, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mekoth, Chitra   +2 more
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Fast CG-Based Methods for Tikhonov--Phillips Regularization

SIAM Journal on Scientific Computing, 1999
The authors study two methods for accelerating the standard conjugate gradient (cg) algorithms for solving a family of systems of the type \[ (A^*A+\alpha I)x= A^* y^\delta. \] In the first method a stopping criterion is developed for the cg-iterates which is linked to the noise level \(\delta\) and the current value of \(\alpha\).
Frommer, Andreas, Maass, Peter
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An Alternative to Tikhonov Regularization for Linear Sampling Methods

Acta Applicandae Mathematicae, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kim, K., Leem, K. H., Pelekanos, G.
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An adaptive Tikhonov regularization method for fluorescence molecular tomography

Medical & Biological Engineering & Computing, 2013
The high degree of absorption and scattering of photons propagating through biological tissues makes fluorescence molecular tomography (FMT) reconstruction a severe ill-posed problem and the reconstructed result is susceptible to noise in the measurements.
Xu, Cao   +6 more
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Tikhonov Regularization Methods for Variational Inequality Problems

Journal of Optimization Theory and Applications, 1999
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On Krylov projection methods and Tikhonov regularization [PDF]

open access: possible, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gazzola S, Novati P, Russo M.R.
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Tikhonov regularization methods for inverse variational inequalities

Optimization Letters, 2013
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Tikhonov Regularization Methods for the Inverse Scalp Electroencephalography

Volume 2: Biomedical and Biotechnology Engineering, 2009
Electroencephalography (EEG) source localization of brain activity is of high diagnostic value. Noninvasive numerical procedures can be developed to help reconstruct the cortical brain activities from the low-spatial-resolution scalp EEG measurement.
Menglu Wu, Xiaolin Chen
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Parameter selection methods for axisymmetric flame tomography through Tikhonov regularization

Applied Optics, 2008
Deconvolution of optically collected axisymmetric flame data is equivalent to solving an ill-posed problem subject to severe error amplification. Tikhonov regularization has recently been shown to be well suited for stabilizing this deconvolution, although the success of this method hinges on choosing a suitable regularization parameter.
Emil O, Akesson, Kyle J, Daun
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A Tikhonov Regularization Method for Image Reconstruction

1993
Many problems of image reconstruction from projection data have the following mathematical form $$ Am = d $$ (1) where m is the unknown model, d is the observed data and A is a known operator. If A is independent of the model m, the tomographic problem is linear; otherwise it is nonlinear.
Chengbin Peng   +2 more
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