Results 1 to 10 of about 24,545 (157)
A New Hybrid Inversion Method for 2D Nuclear Magnetic Resonance Combining TSVD and Tikhonov Regularization [PDF]
Journal of Imaging, 2021 This paper is concerned with the reconstruction of relaxation time distributions in Nuclear Magnetic Resonance (NMR) relaxometry. This is a large-scale and ill-posed inverse problem with many potential applications in biology, medicine, chemistry, and ...
Germana Landi +2 more
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Optimal Tikhonov regularization for DEER spectroscopy. [PDF]
J Magn Reson, 2018 Tikhonov regularization is the most commonly used method for extracting distance distributions from experimental double electron-electron resonance (DEER) spectroscopy data. This method requires the selection of a regularization parameter, α, and a regularization operator, L.
Edwards TH, Stoll S.
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Extrapolation of Tikhonov regularization method
Mathematical Modelling and Analysis, 2010 We consider regularization of linear ill‐posed problem Au = f with noisy data fδ, ¦fδ - f¦≤ δ . The approximate solution is computed as the extrapolated Tikhonov approximation, which is a linear combination of n ≥ 2 Tikhonov approximations with different
Uno Hämarik, Reimo Palm, Toomas Raus
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The Application of Piecewise Regularization Reconstruction to the Calibration of Strain Beams [PDF]
SensorsStandard beams are mainly used for the calibration of strain sensors using their load reconstruction models. However, as an ill-posed inverse problem, the solution to these models often fails to converge, especially when dealing with dynamic loads of ...
Jingjing Liu +7 more
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A Posteriori Fractional Tikhonov Regularization Method for the Problem of Analytic Continuation
Mathematics, 2021 In this paper, the numerical analytic continuation problem is addressed and a fractional Tikhonov regularization method is proposed. The fractional Tikhonov regularization not only overcomes the difficulty of analyzing the ill-posedness of the ...
Xuemin Xue, Xiangtuan Xiong
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Algorithms, 2023 This paper aims to determine whether regularization improves image reconstruction in electrical impedance tomography (EIT) using a radial basis network. The primary purpose is to investigate the effect of regularization to estimate the network parameters
Chowdhury Abrar Faiyaz +4 more
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An Improved Tikhonov-Regularized Variable Projection Algorithm for Separable Nonlinear Least Squares
Axioms, 2021 In this work, we investigate the ill-conditioned problem of a separable, nonlinear least squares model by using the variable projection method. Based on the truncated singular value decomposition method and the Tikhonov regularization method, we propose ...
Hua Guo, Guolin Liu, Luyao Wang
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Tikhonov Regularization within Ensemble Kalman Inversion [PDF]
SIAM 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
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Mathematical and numerical modeling of inverse heat conduction problem [PDF]
INCAS Bulletin, 2014 The present paper refers to the assessment of three numerical methods for solving the inverse heat conduction problem: the Alifanov’s iterative regularization method, the Tikhonov local regularization method and the Tikhonov equation regularization ...
Sterian DANAILA, Alina-Ioana CHIRA
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Multi-parameter Tikhonov regularization [PDF]
Methods and Applications of Analysis, 2011 We study multi-parameter Tikhonov regularization, i.e., with multiple penalties. Such models are useful when the sought-for solution exhibits several distinct features simultaneously. Two choice rules, i.e., discrepancy principle and balancing principle, are studied for choosing an appropriate (vector-valued) regularization parameter, and some ...
Ito, Kazufumi +2 more
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