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Variational Quantum Singular Value Decomposition [PDF]
Quantum, 2021 Singular value decomposition is central to many problems in engineering and scientific fields. Several quantum algorithms have been proposed to determine the singular values and their associated singular vectors of a given matrix.
Xin Wang, Zhixin Song, Youle Wang
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Singular value decomposition-based gait characterization [PDF]
Heliyon, 2022 Background: Human gait varies based on personal characteristics, the existence of walking problems, or variability of gait parameters. Identifying the sources of variations is significant in detecting walking problems, designing orthotic/prosthetic ...
Cem Guzelbulut +2 more
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Privacy-Preserving Federated Singular Value Decomposition
Applied Sciences, 2023 Singular value decomposition (SVD) is a fundamental technique widely used in various applications, such as recommendation systems and principal component analyses.
Bowen Liu, Balázs Pejó, Qiang Tang
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Singular Value Decomposition of Spatial Matrices
Современные информационные технологии и IT-образование, 2022 Singular value decomposition is a basic building block which is used in solution of many different problems. In cases when dimensionality of a problem exceeds two, a generalization of a singular value decomposition – tensor decompositions – are used ...
Pavel Iljin, Tatiana Samoilova
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Watermark Based on Singular Value Decomposition
مجلة بغداد للعلوم, 2023 Watermarking operation can be defined as a process of embedding special wanted and reversible information in important secure files to protect the ownership or information of the wanted cover file based on the proposed singular value decomposition (SVD)
Ali Abdulazeez Mohammed Baqer Qazzaz +1 more
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Applied Sciences, 2022 The rub-impact fault, which occurs in the aeroengine, can cause frequency modulation (FM) in its vibration signal. Oscillated instantaneous frequency (IF) is a phenomenon of such a modulation mode, which carries critical fault information from the ...
Peng Zhang +7 more
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Truncated singular value decomposition in ripped photo recovery [PDF]
ITM Web of Conferences, 2021 Singular value decomposition (SVD) is one of the most useful matrix decompositions in linear algebra. Here, a novel application of SVD in recovering ripped photos was exploited. Recovery was done by applying truncated SVD iteratively.
Lem Kong Hoong
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Scalability of k-Tridiagonal Matrix Singular Value Decomposition
Mathematics, 2021 Singular value decomposition has recently seen a great theoretical improvement for k-tridiagonal matrices, obtaining a considerable speed up over all previous implementations, but at the cost of not ordering the singular values.
Andrei Tănăsescu +3 more
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Partial Singular Value Assignment for Large-Scale Systems
Axioms, 2023 The partial singular value assignment problem stems from the development of observers for discrete-time descriptor systems and the resolution of ordinary differential equations.
Yiting Huang, Qiong Tang, Bo Yu
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Research on a Noise Reduction Method Based on Multi-Resolution Singular Value Decomposition
Applied Sciences, 2020 Reducing noise pollution in signals is of great significance in the field of signal detection. In order to reduce the noise in the signal and improve the signal-to-noise ratio (SNR), this paper takes the singular value decomposition theory as the ...
Gang Zhang +6 more
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