Results 11 to 20 of about 13,343 (226)
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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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 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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Utilizing SVD and VMD for Denoising Non-Stationary Signals of Roller Bearings
Sensors, 2021 In view of the fact that vibration signals of rolling bearings are much contaminated by noise in the early failure period, this paper presents a new denoising SVD-VMD method by combining singular value decomposition (SVD) and variational mode ...
Qinghua Wang +4 more
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An Improved Unscented Kalman Filter Algorithm for Radar Azimuth Mutation
International Journal of Aerospace Engineering, 2020 An improved UKF (Unscented Kalman Filter) algorithm is proposed to solve the problem of radar azimuth mutation. Since the radar azimuth angle will restart to count after each revolution of the radar, and when the aircraft just passes the abrupt angle ...
Dazhang You +5 more
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A Novel Wheelset Bearing Fault Diagnosis Method Integrated CEEMDAN, Periodic Segment Matrix, and SVD
Shock and Vibration, 2018 A novel fault diagnosis method, named CPS, is proposed based on the combination of CEEMDAN (complete ensemble empirical mode decomposition with adaptive noise), PSM (periodic segment matrix), and SVD (singular value decomposition). Firstly, the collected
Chenguang Huang +3 more
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Harmonic detection algorithm based on improved SVD and Prony
Dianzi Jishu Yingyong, 2019 An improved algorithm based on singular value decomposition(SVD) and Prony is proposed to solve the problem that the traditional Prony algorithm is not very accurate because it is sensitive to noise during harmonic and inter-harmonic detection.
Ying Jun, Zhu Yunpeng, He Chao
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svds-C: A multi-thread C code for computing truncated singular value decomposition
SoftwareX, 2023 This article presents svds-C, an open-source and high-performance C program for accurately and robustly computing truncated SVD, e.g. computing several largest singular values and corresponding singular vectors. We have re-implemented the algorithm of svds in Matlab in C based on MKL or OpenBLAS and multi-thread computing to obtain the parallel program
Xu Feng, Wenjian Yu, Yuyang Xie
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Singular Value Decomposition Approaches in A Correspondence Analysis with The Use of R
Folia Oeconomica Stetinensia, 2018 The aim of a correspondence analysis is the graphical representation of the categories of variables in one frame of reference. This visualization is possible due to the decomposition of the basic matrix with the use of Singular Value Decomposition (SVD).
Brzezińska Justyna
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