Results 171 to 180 of about 11,051,325 (215)

On Sampling-Times-Independent Identification of Relaxation Time and Frequency Spectra Models of Viscoelastic Materials Using Stress Relaxation Experiment Data. [PDF]

Materials (Basel)
Stankiewicz A, Juściński S, Błażewicz-Woźniak M.   +2 more
europepmc   +1 more source

Exact sequence interpolation with transformers. [PDF]

Math Found Mach Learn
Alcalde A, Fantuzzi G, Zuazua E.
europepmc   +1 more source

Machine learning framework for oxytetracycline removal using nanostructured cupric oxide supported on magnetic chitosan alginate biocomposite.

Sci Rep
Rasoulzadeh H, Azarpira H, Pourakbar M, Sheikhmohammadi A, Rezagholizade-Shirvan A.   +4 more
europepmc   +1 more source

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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.
Chitra Mekoth, Santhosh George, P. Jidesh   +2 more
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Iterated Tikhonov regularization with a general penalty term

Numerical Linear Algebra With Applications, 2017
Tikhonov regularization is one of the most popular approaches to solving linear discrete ill-posed problems. The choice of the regularization matrix may significantly affect the quality of the computed solution.
Marco Donatelli, Alessandro Buccini, Lothar Reichel   +2 more
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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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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 \(\alpha\).
Andreas Frommer, Peter Maass
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An Improved Tikhonov Regularization Method for Conductivity Tomography Imaging

2008 International Symposium on Computer Science and Computational Technology, 2008
Discretizations of inverse problem lead to systems of linear equations with a highly ill-conditioned coefficient matrix, and in order to compute stable solutions to these systems it is necessary to apply regularization methods. This paper compares our improved Tikhonov regularization algorithm to several existing regularization methods, which are ...
Baobin Feng, Wenjuan Wang, Junxing Cao
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Tomosar Focusing by Means of A Variant of Tikhonov Regularized Method

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Tomographic synthetic aperture radar (TomoSAR) imaging has shown great potential in the three dimensional SAR focusing in recent years. One practical challenge is that the spatial separation of the multi-pass system is always nonuniform and also the number of tracks is very limited, thus leading to the focusing results inaccurate. Conventional Tikhonov
Jinwei Xie, Zhibin Wang, Zhenfang Li
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Tikhonov regularization methods for inverse variational inequalities

Optimization Letters, 2013
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