Results 21 to 30 of about 110,162 (274)
Image-denoising algorithm based on improved K-singular value decomposition and atom optimization
CAAI Transactions on Intelligence Technology, 2021 The traditional K ‐ singular value decomposition (K ‐ SVD) algorithm has poor image ‐ denoising performance under strong noise. An image ‐ denoising algorithm is proposed based on improved K ‐ SVD and dictionary atom optimization.
Rui Chen +3 more
semanticscholar +1 more source
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
doaj +1 more source
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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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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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
doaj +1 more source
AIMS Mathematics, 2023 The singular value decomposition (SVD) is an important tool in matrix theory and numerical linear algebra. Research on the efficient numerical algorithms for computing the SVD of a matrix is extensive in the past decades.
Yonghong Duan, Ruiping Wen
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Singular Value Decomposition (SVD) Berdasarkan Intensitas Pencahayaannya Untuk Pengenal Wajah [PDF]
Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer, 2021 Singular Value Decomposition (SVD) is a method that can be used for biometric systems, where the biometric system is a system for identification by using physical features or human limbs such as fingerprints, eye retina, face, and others. This writing aims to recognize faces based on the intensity of their lighting using SVD. The use of SVD is done
Samsurizal Samsurizal +2 more
openaire +1 more source
A Constructive Algorithm for Decomposing a Tensor into a Finite Sum of Orthonormal Rank-1 Terms [PDF]
, 2015 We propose a constructive algorithm that decomposes an arbitrary real tensor into a finite sum of orthonormal rank-1 outer products. The algorithm, named TTr1SVD, works by converting the tensor into a tensor-train rank-1 (TTr1) series via the singular ...
Batselier, Kim, Liu, Haotian, Wong, Ngai
core +3 more sources
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
doaj +1 more source
Energies, 2021 Partial discharge detection is an important means of insulation diagnosis of electrical equipment. To effectively suppress the periodic narrowband and white noise interferences in the process of partial discharge detection, a partial discharge ...
Linao Li, Xinlao Wei
semanticscholar +1 more source