Results 261 to 270 of about 1,327,176 (293)

Smoothing parameter selection using the L-curve

2012
The L-curve method has been used to select the penalty parameter in ridge regression. We show that it is also very attractive for smoothing, because of its low computational load. Surprisingly, it also is almost insensitive to serial correlation.
Frasso, Gianluca, Eilers, Paul H.C.
openaire   +1 more source

Regularised synthesis of the magnetic field using the L-curve approach

International Journal of Applied Electromagnetics and Mechanics, 2005
Ill-posed problems occur frequently in science and engineering. Regularisation methods are used for computing stable solutions to the ill-posed problems. The purpose of regularisation is to incorporate more information about the desired solution in order to stabilise the problem and find a useful and stable solution.
Krawczyk-Stando, Dorota, Rudnicki, Marek
openaire   +1 more source

Shape reconstruction of a 2D-elastic penetrable object via the L-curve method

Journal of Inverse and Ill-Posed Problems, 2006
Summary: We discuss an inversion algorithm which combined with the \(L\)-curve criterion for the selection of the regularization parameter, effectively yields shape reconstructions of penetrable obstacles. The required scattered elastic field is generated by either a \(P\) or \(S\)-incident wave.
Pelekanos, G., Sevroglou, V.
openaire   +1 more source

Analysis of Discrete Ill-Posed Problems by Means of the L-Curve

SIAM Review, 1992
This paper is concerned with the parameter choice problem in regularization methods for linear ill-posed problems. A convenient way for studying this problem is to plot - for various regularization parameters - the (semi)norm of the regularized solution versus the norm of the corresponding residual.
openaire   +1 more source

Optimal regularization of the inverse-heat conduction problem using the L-curve

International Journal of Numerical Methods for Heat & Fluid Flow, 1994
Solving the inverse heat conduction using Tikhonov regularization requires the selection of an optimal smoothing parameter. One popular method for choosing the smoothing parameter is the generalized cross-validation method. This method works very well but is computationally expensive.
David M. Trujillo, Henry R. Busby
openaire   +1 more source

Comparison of L-curve and LOOCV depth profiles from TAARXPS data

Journal of Electron Spectroscopy and Related Phenomena, 2017
Abstract Time and angle resolved X-ray photoelectron spectroscopy (TAARXPS) data, obtained from polystyrene samples exposed to an oxygen/helium plasma, have been interpreted using 1st order Tikhonov regularization to smooth the extracted depth profiles.
openaire   +1 more source

Regularization in PNAH by means of L-curve

2005
Planar Near-field Acoustic Holography (PNAH) is an acoustic imaging technique based on the inverse solution of the wave equation. Planar acoustic information at a certain distance from the source of interest, known as the hologram, is used as input to signal process based on Fourier transforms understrict boundary conditions.
Scholte, R., Roozen, N.B., Lopez Arteaga, I.   +2 more
openaire   +1 more source

Copyright's L Curve Problem

SSRN Electronic Journal, 2019
openaire   +1 more source

B-L Curve of Cotton Yarns

Textile Research Journal, 1965
openaire   +1 more source

Tailoring microstructure and texture of Mg–3Al–1Zn alloy sheets through curve extrusion process for achieving low planar anisotropy

Journal of Materials Science and Technology, 2022
Bin Jiang
exaly