Results 31 to 40 of about 101,252 (223)

Regularization by Intrinsic Plasticity and its Synergies with Recurrence for Random Projection Methods [PDF]

open access: yes, 2012
Neumann K, Emmerich C, Steil JJ. Regularization by Intrinsic Plasticity and its Synergies with Recurrence for Random Projection Methods. Journal of Intelligent Learning Systems and Applications. 2012;4(3):230-246.Neural networks based on high-dimensional
Emmerich, Christian   +2 more
core   +1 more source

An Exponential Filtering Based Inversion Method for Microwave Imaging [PDF]

open access: yesRadioengineering, 2021
In this paper, a new methodology based on the exponential filtering of singular values is adopted to solve the linear ill-posed problem of microwave imaging.
A. Magdum   +2 more
doaj  

New Robust Regularized Shrinkage Regression for High-Dimensional Image Recovery and Alignment via Affine Transformation and Tikhonov Regularization

open access: yesInternational Journal of Mathematics and Mathematical Sciences, 2020
In this work, a new robust regularized shrinkage regression method is proposed to recover and align high-dimensional images via affine transformation and Tikhonov regularization. To be more resilient with occlusions and illuminations, outliers, and heavy
Habte Tadesse Likassa   +2 more
doaj   +1 more source

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

Reconstruction of Mercury's internal magnetic field beyond the octupole [PDF]

open access: yesAnnales Geophysicae, 2022
The reconstruction of Mercury's internal magnetic field enables us to take a look into the inner heart of Mercury. In view of the BepiColombo mission, Mercury's magnetosphere is simulated using a hybrid plasma code, and the multipoles of the internal ...
S. Toepfer   +10 more
doaj   +1 more source

Temperature dependence of relaxation spectra for highly hydrated gluten networks [PDF]

open access: yes, 2010
In the present investigation, the temperature dependence (0e50 C) of the relaxation spectrum of hydrated gluten was studied using novel numerical algorithms. Tikhonov regularization, in conjunction with the L-curve criterion for optimal calculation of
Kasapis, Stefan, Kontogiorgos, Vassilis
core   +1 more source

A parameter choice for Tikhonov regularization for solving nonlinear inverse problems leading to optimal convergence rates [PDF]

open access: yes, 1993
summary:We give a derivation of an a-posteriori strategy for choosing the regularization parameter in Tikhonov regularization for solving nonlinear ill-posed problems, which leads to optimal convergence rates.
Scherzer, Otmar
core   +1 more source

Node-Adaptive Regularization for Graph Signal Reconstruction

open access: yesIEEE Open Journal of Signal Processing, 2021
A critical task in graph signal processing is to estimate the true signal from noisy observations over a subset of nodes, also known as the reconstruction problem.
Maosheng Yang   +3 more
doaj   +1 more source

Adaptive Tikhonov regularization and dynamic control points for accurate shape parameter control of plasmas

open access: yesNuclear Fusion, 2023
Precise control of plasma shape parameters, such as elongation and triangularity is duly needed to achieve high-performance tokamak plasmas, for which we propose adaptive search schemes of (1) optimum regularization parameter for the Tikhonov ...
S. Inoue   +4 more
doaj   +1 more source

Convergence analysis of Tikhonov regularization for non-linear statistical inverse learning problems [PDF]

open access: yes, 2019
We study a non-linear statistical inverse learning problem, where we observe the noisy image of a quantity through a non-linear operator at some random design points.
Mathé, Peter   +2 more
core   +1 more source

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