Results 211 to 220 of about 110,162 (274)
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Differentiable Singular Value Decomposition (Svd)
Mechanical Systems and Signal ProcessingRohit Sunil Kanchi, Sicheng He
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International Journal of Information Technology and Decision Making, 2021
In recommender systems, Collaborative Filtering (CF) plays an essential role in promoting recommendation services. The conventional CF approach has limitations, namely data sparsity and cold-start.
Taushif Anwar, V. Uma, Gautam Srivastava
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In recommender systems, Collaborative Filtering (CF) plays an essential role in promoting recommendation services. The conventional CF approach has limitations, namely data sparsity and cold-start.
Taushif Anwar, V. Uma, Gautam Srivastava
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A Bearing Fault Diagnosis Method Based on Enhanced Singular Value Decomposition
IEEE Transactions on Industrial Informatics, 2021For the two shortcomings of singular value decomposition (SVD), the determination of the reconstruction order and the poor noise reduction ability, an enhanced SVD is introduced in this article.
Hua Li, Tao Liu, Xing Wu, Qing Chen
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IEEE Transactions on Power Delivery, 2022
The modular multilevel converter-based high voltage direct current transmission (MMC-HVDC) technology has become an effective integrating method for large-capacity offshore wind farms.
Liming Zheng +4 more
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The modular multilevel converter-based high voltage direct current transmission (MMC-HVDC) technology has become an effective integrating method for large-capacity offshore wind farms.
Liming Zheng +4 more
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2021 International Conference on Information Technology (ICIT), 2021
This paper introduces singular value decomposition (SVD), a major matrix decomposition technique. SVD serves as the underlining computational engine of many other techniques such as principal component analysis (PCA), eigen decomposition, matrix ...
Yousef Jaradat +4 more
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This paper introduces singular value decomposition (SVD), a major matrix decomposition technique. SVD serves as the underlining computational engine of many other techniques such as principal component analysis (PCA), eigen decomposition, matrix ...
Yousef Jaradat +4 more
semanticscholar +1 more source
Neural Embedding Singular Value Decomposition for Collaborative Filtering
IEEE Transactions on Neural Networks and Learning Systems, 2021Singular value decomposition (SVD) is one of the most effective algorithms in recommender systems (RSs). Due to the iterative nature of SVD algorithms, one big challenge is initialization that has a major impact on the convergence and performance of RSs.
Tianlin Huang +4 more
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Robust tensor completion using transformed tensor singular value decomposition
Numerical Linear Algebra with Applications, 2020In this article, we study robust tensor completion by using transformed tensor singular value decomposition (SVD), which employs unitary transform matrices instead of discrete Fourier transform matrix that is used in the traditional tensor SVD.
Guang-Jing Song, M. Ng, Xiongjun Zhang
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Singular Value Decomposition (SVD) based Image Tamper Detection Scheme
2020 International Conference on Inventive Computation Technologies (ICICT), 2020Image authentication techniques are basically used to check whether the received document is accurate or actual as it was transmitted by the source node or not. Image authentication ensures the integrity of the digital images and identify the ownership of the copyright of the digital images. Singular Value Decomposition (SVD) is method based on spatial
Sandeep Kaur, Alka Jindal
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IEEE Transactions on Instrumentation and Measurement, 2020
Online partial discharge (PD) monitoring is an important means to detect insulation deterioration. However, it is difficult to extract the PD signal due to various interferences in the field.
Jun Zhong +5 more
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Online partial discharge (PD) monitoring is an important means to detect insulation deterioration. However, it is difficult to extract the PD signal due to various interferences in the field.
Jun Zhong +5 more
semanticscholar +1 more source
Analysis of scintigrams by singular value decomposition (SVD) technique
Annals of Nuclear Medicine, 1994The singular value decomposition (SVD) method is presented as a potential tool for analyzing gamma camera images. Mathematically image analysis is a study of matrixes as the standard scintigram is a digitized matrix presentation of the recorded photon fluence from radioactivity of the object.
S E, Savolainen, B K, Liewendahl
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