Results 91 to 100 of about 24,593 (203)
Influence of the Tikhonov Regularization Parameter on the Accuracy of the Inverse Problem in Electrocardiography. [PDF]
Wang T, Karel J, Bonizzi P, Peeters RLM.
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A modified Tikhonov regularization method
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Yang, Xiao-Juan, Wang, Li
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Denoising Multi‐Color QR Codes and Stiefel‐Valued Data by Relaxed Regularizations
ABSTRACT The handling of manifold‐valued data, for instance, plays a central role in color restoration tasks relying on circle‐ or sphere‐valued color models, in the study of rotational or directional information related to the special orthogonal group, and in Gaussian image processing, where the pixel statistics are interpreted as values on the ...
Robert Beinert, Jonas Bresch
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Computation of distribution of relaxation times by Tikhonov regularization for Li ion batteries: usage of L-curve method. [PDF]
Paul T, Chi PW, Wu PM, Wu MK.
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Abstract Simultaneous analyses of complementary GNSS and InSAR measurements may lead to breakthroughs in our understanding of crustal deformation. We present an algorithm that combines InSAR with GNSS measurements, in which the GNSS data can be used either as original station velocities or as an interpolated and smoothed velocity field, to estimate ...
Jeonghyeop Kim +4 more
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To systematically and thoroughly analyze the sensitivity and reliability of the MSBAS regularization for the estimation of surface deformation over a mine in combination with an application example, this study processed 101 Sentinel-1A/B SAR images ...
Qiuxiang Tao +5 more
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On a Level-Set Method for Ill-Posed Problems with Piecewise Nonconstant Coefficients
We investigate a level-set-type method for solving ill-posed problems, with the assumption that the solutions are piecewise, but not necessarily constant functions with unknown level sets and unknown level values.
A. De Cezaro
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Wavelet-Accelerated Tikhonov-Phillips Regularization with Applications [PDF]
Many technical and physical problems can be mathematically modeled by operator equations (1) of the first kind, $$Ax = y$$ , where x is the searched-for information under observed data y. We mention only a few typical examples: medical imaging, see e.g. [16, 20], and inverse scattering problems, see e.g. [6].
Rieder, A., Maaß, P.
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Demonstration of a family of X‐ray dark‐field retrieval approaches on a common set of samples
This study aims to guide users of dark‐field imaging in selecting the most suitable technique for their imaging goals. To this end, we provide a summary table and highlight opportunities for future research into the sources of dark‐field contrast across emerging methods.There are various imaging setups capable of capturing dark‐field images, each with ...
Samantha J. Alloo +5 more
wiley +1 more source
A PROPOSAL FOR REGULARIZED INVERSION FOR AN ILL-CONDITIONED DECONVOLUTION OPERATOR
From the inverse problem theory aspect, deconvolution can be understood as the linear inversion of an ill-posed and ill-conditioned problem. The ill-conditioned property of the deconvolution operator make the solution of inverse problem sensitive to ...
Herling Gonzalez +2 more
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