Results 11 to 20 of about 110,162 (274)
Singular value decomposition (Svd) [PDF]
Data-Driven Science and Engineering, 1998 S. Brunton, J. Kutz
semanticscholar +8 more sources
Partial Discharge Signal Extraction Method Based on EDSSV and Low Rank RBF Neural Network
IEEE Access, 2021 The detection process of partial discharge (PD) ultra-high frequency (UHF) signal is easily affected by white noise and periodic narrowband noise, which hinder the fault diagnosis of high-voltage electrical appliances.
Xiaoli Yang +4 more
doaj +1 more source
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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Color to Grayscale Image Conversion Based on Singular Value Decomposition
IEEE Access, 2023 Color information is useless for distinguishing significant edges and features in numerous applications. In image processing, a gray image discards much-unrequired data in a color image.
Zaid Nidhal Khudhair +6 more
semanticscholar +1 more source
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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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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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 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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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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