Results 51 to 60 of about 7,882 (230)

The Tikhonov regularization method in elastoplasticity

open access: yesApplied Mathematical Modelling, 2012
The numeric simulation of the mechanical behaviour of industrial materials is widely used in the companies for viability verification, improvement and optimization of designs. The eslastoplastic models have been used for forecast of the mechanical behaviour of materials of the most several natures (see [1]).
Azikri de Deus, Hilbeth P.   +3 more
openaire   +3 more sources

Signal Restoration Combining Modified Tikhonov Regularization and Preconditioning Technology

open access: yesIEEE Access, 2017
The purpose of signal restoration is to acquire a clean signal from the degraded signal which contains blur and noise. In this paper, a modified Tikhonov regularization method based on the standard Tikhonov regularization matrix is proposed, and the ...
Hong-Xia Dou   +3 more
doaj   +1 more source

A modified Tikhonov regularization for unknown source in space fractional diffusion equation

open access: yesOpen Mathematics, 2022
In this article, we consider the identification of an unknown steady source in a class of fractional diffusion equations. A modified Tikhonov regularization method based on Hermite expansion is presented to deal with the ill-posedness of the problem.
Yu Kai, Gong Benxue, Zhao Zhenyu
doaj   +1 more source

Prediction of propagated wave profiles based on point measurement

open access: yesInternational Journal of Naval Architecture and Ocean Engineering, 2014
This study presents the prediction of propagated wave profiles using the wave information at a fixed point. The fixed points can be fixed in either space or time.
Lee Sang-Beom   +3 more
doaj   +3 more sources

Wasserstein Diffusion Tikhonov Regularization

open access: yesCoRR, 2019
We propose regularization strategies for learning discriminative models that are robust to in-class variations of the input data. We use the Wasserstein-2 geometry to capture semantically meaningful neighborhoods in the space of images, and define a corresponding input-dependent additive noise data augmentation model.
Alex Tong Lin   +3 more
openaire   +3 more sources

A modified Tikhonov regularization method

open access: yesJournal of Computational and Applied Mathematics, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xiao-Juan Yang, Li Wang
openaire   +2 more sources

DISCRETIZATION ERROR ANALYSIS FOR TIKHONOV REGULARIZATION [PDF]

open access: yesAnalysis and Applications, 2006
We study the discretization of inverse problems defined by a Carleman operator. In particular, we develop a discretization strategy for this class of inverse problems and we give a convergence analysis. Learning from examples, as well as the discretization of integral equations, can be analyzed in our setting.
DE VITO, ERNESTO   +2 more
openaire   +2 more sources

Particle swarm optimization method for parameter selecting in Tikhonov regularization method for solving inverse problems

open access: yese-Prime: Advances in Electrical Engineering, Electronics and Energy
In this article the Tikhonov method used as a regularization technique for solving the inverse problem liner operator equation of the first kind with noisy and noise-free data. We also provide the Tikhonov method's essential analysis for tackling inverse
H.K. Al-Mahdawi, A.S. Alhumaima
doaj   +1 more source

A Fast Iterative Shrinkage/Thresholding Algorithm via Laplace Norm for Sound Source Identification

open access: yesIEEE Access, 2020
As a powerful tool, near-field acoustical holography (NAH) recognizes the sound source effectively. The traditional equivalent source method (ESM) calculated by the Tikhonov regularization method could be available in the low-frequency band.
Linsen Huang   +4 more
doaj   +1 more source

Tikhonov Regularization within Ensemble Kalman Inversion [PDF]

open access: yesSIAM Journal on Numerical Analysis, 2020
Ensemble Kalman inversion is a parallelizable methodology for solving inverse or parameter estimation problems. Although it is based on ideas from Kalman filtering, it may be viewed as a derivative-free optimization method. In its most basic form it regularizes ill-posed inverse problems through the subspace property: the solution found is in the ...
Neil K. Chada   +2 more
openaire   +4 more sources

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