Unbiased predictive risk estimation of the Tikhonov regularization parameter: convergence with increasing rank approximations of the singular value decomposition
Sign Up to like & getrecommendations! Published in 2019 at "BIT Numerical Mathematics"
DOI: 10.1007/s10543-019-00762-7
Abstract: The truncated singular value decomposition may be used to find the solution of linear discrete ill-posed problems in conjunction with Tikhonov regularization and requires the estimation of a regularization parameter that balances between the sizes… read more here.
Keywords: regularization; regularization parameter; singular value; value decomposition ... See more keywords
High-order total variation-based Poissonian image deconvolution with spatially adapted regularization parameter
Sign Up to like & getrecommendations! Published in 2017 at "Applied Mathematical Modelling"
DOI: 10.1016/j.apm.2017.01.009
Abstract: Abstract Images captured by image acquisition systems using photon-counting devices such as astronomical imaging, positron emission tomography and confocal microscopy imaging, are often contaminated by Poisson noise. Total variation (TV) regularization, which is a classic… read more here.
Keywords: regularization parameter; image; total variation; regularization ... See more keywords
Iterative minimal residual method provides optimal regularization parameter for extreme learning machines
Sign Up to like & getrecommendations! Published in 2019 at "Results in Physics"
DOI: 10.1016/j.rinp.2019.02.018
Abstract: Abstract Extreme Learning Machine (ELM) is a single hidden layer feed-forward neural network with the learning speed is much faster than the traditional neural network architecture. The main reason is attributed to the application of… read more here.
Keywords: regularization parameter; method; regularization; extreme learning ... See more keywords
Comparative studies on the criteria for regularization parameter selection based on moving force identification
Sign Up to like & getrecommendations! Published in 2020 at "Inverse Problems in Science and Engineering"
DOI: 10.1080/17415977.2020.1781848
Abstract: The studies on inverse problems exist extensively in aerospace, mechanical, identification, detection, scanning imaging and other fields. Its ill-posed characteristics often lead to large oscillations in the solution of the inverse problem. In this study,… read more here.
Keywords: identification; criterion; truncating point; regularization parameter ... See more keywords
A nonconvex penalization algorithm with automatic choice of the regularization parameter in sparse imaging
Sign Up to like & getrecommendations! Published in 2019 at "Inverse Problems"
DOI: 10.1088/1361-6420/ab1c6b
Abstract: This paper introduces an efficient method for solving nonconvex penalized minimization problems. The topic is relevant in many imaging problems characterized by sparse data. The proposed method originates from the iterative reweighting l 1 scheme,… read more here.
Keywords: parameter; regularization parameter; method; sparse imaging ... See more keywords
Hyperspectral Image Super-Resolution via Deep Prior Regularization With Parameter Estimation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2021.3078559
Abstract: Hyperspectral image (HSI) super-resolution is commonly used to overcome the hardware limitations of existing hyperspectral imaging systems on spatial resolution. It fuses a low-resolution (LR) HSI and a high-resolution (HR) conventional image of the same… read more here.
Keywords: resolution; regularization parameter; hyperspectral image; super resolution ... See more keywords
Choice of Regularization Parameter in Adaptive Filtering Problems
Sign Up to like & getrecommendations! Published in 2019 at "Computational Mathematics and Mathematical Physics"
DOI: 10.1134/s0965542519060101
Abstract: The paper proposes a new method for choosing a regularization parameter when solving an integral equation of convolution type in problems of adaptive filtering. This method is based on minimizing the deviation of the phase… read more here.
Keywords: regularization parameter; method; choice regularization; regularization ... See more keywords
A New Method for Determining Optimal Regularization Parameter in Near-Field Acoustic Holography
Sign Up to like & getrecommendations! Published in 2018 at "Shock and Vibration"
DOI: 10.1155/2018/7303294
Abstract: Tikhonov regularization method is effective in stabilizing reconstruction process of the near-field acoustic holography (NAH) based on the equivalent source method (ESM), and the selection of the optimal regularization parameter is a key problem that… read more here.
Keywords: regularization; source; method; optimal regularization ... See more keywords
Considering New Regularization Parameter-Choice Techniques for the Tikhonov Method to Improve the Accuracy of Electrocardiographic Imaging
Sign Up to like & getrecommendations! Published in 2019 at "Frontiers in Physiology"
DOI: 10.3389/fphys.2019.00273
Abstract: The electrocardiographic imaging (ECGI) inverse problem highly relies on adding constraints, a process called regularization, as the problem is ill-posed. When there are no prior information provided about the unknown epicardial potentials, the Tikhonov regularization… read more here.
Keywords: regularization parameter; electrocardiographic imaging; parameter choice; regularization ... See more keywords