Results 11 to 20 of about 71,044 (233)
Empirical Evaluation of Four Tensor Decomposition Algorithms [PDF]
, 2007 Higher-order tensor decompositions are analogous to the familiar Singular Value Decomposition (SVD), but they transcend the limitations of matrices (second-order tensors).
Turney, Peter D.
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Reseaech on identification of caving coal and rock traits
Gong-kuang zidonghua, 2017 In order to recognize caving coal and rock traits in fully mechanized caving face, an identification method based on continuous wavelet transform and improved singular value decomposition (SVD) was proposed.
LI Yiming, FU Shichen, LI Rui, WU Miao
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Two-Channel Information Fusion Weak Signal Detection Based on Correntropy Method
Applied Sciences, 2022 In recent years, as a simple and effective method of noise reduction, singular value decomposition (SVD) has been widely concerned and applied. The idea of SVD for denoising is mainly to remove singular components (SCs) with small singular value (SV ...
Siqi Gong +5 more
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Dynamic RBC-To-Membrane Ratio in <sup>129</sup>Xe MRI: A Biomarker of Decreased Lung Function in Pulmonary and Vascular Diseases. [PDF]
Magn Reson MedABSTRACT Purpose To present a method for quantifying dissolved 129Xe spectroscopy using singular value decomposition (SVD) and a dynamic red blood cell (RBC)/membrane ratio as a biomarker of disease. Methods A spectroscopic sequence was performed in 45 subjects (27 healthy, 12 dyspnea of unknown origin [DUO], and 6 pulmonary hypertension [PH ...
García Delgado GM +8 more
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Energies, 2022 This paper proposes a denoising method of vibration signal based on improved multiresolution singular value decomposition (IMRSVD) and effective component selection.
Xihui Chen +3 more
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Very Large-Scale Singular Value Decomposition Using Tensor Train Networks [PDF]
, 2014 We propose new algorithms for singular value decomposition (SVD) of very large-scale matrices based on a low-rank tensor approximation technique called the tensor train (TT) format. The proposed algorithms can compute several dominant singular values and
Cichocki, Andrzej, Lee, Namgil
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A Novel Watermarking Method using Hadamard Matrix Quantization
Journal of ICT Research and Applications, 2020 One of the most used watermarking algorithms is Singular Value Decomposition (SVD), which has a balanced level of imperceptibility and robustness. However, SVD uses a singular matrix for embedding and two orthogonal matrices for reconstruction, which is ...
Prajanto Wahyu Adi, Pramudi Arsiwi
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A Geometric Perspective on the Singular Value Decomposition [PDF]
, 2015 This is an introductory survey, from a geometric perspective, on the Singular Value Decomposition (SVD) for real matrices, focusing on the role of the Terracini Lemma.
Ottaviani, Giorgio, Paoletti, Raffaella
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A Star Sensor On-Orbit Calibration Method Based on Singular Value Decomposition
Sensors, 2019 The navigation accuracy of a star sensor depends on the estimation accuracy of its optical parameters, and so, the parameters should be updated in real time to obtain the best performance. Current on-orbit calibration methods for star sensors mainly rely
Liang Wu +5 more
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Early stopping for statistical inverse problems via truncated SVD estimation [PDF]
, 2018 We consider truncated SVD (or spectral cut-off, projection) estimators for a prototypical statistical inverse problem in dimension $D$. Since calculating the singular value decomposition (SVD) only for the largest singular values is much less costly than
Blanchard, Gilles +2 more
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