Results 21 to 30 of about 71,463 (232)

An Improved Unscented Kalman Filter Algorithm for Radar Azimuth Mutation

open access: yesInternational 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

Utilizing SVD and VMD for Denoising Non-Stationary Signals of Roller Bearings

open access: yesSensors, 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
doaj   +1 more source

The Hessian biased singular value decomposition method for optimization and analysis of force fields [PDF]

open access: yes, 1996
We present methodology (HBFF/SVD) for optimizing the form and parameters of force fields (FF) for molecular dynamics simulations through utilizing information about properties such as the geometry, Hessian, polarizability, stress (crystals), and elastic ...
Dasgupta, Siddharth   +2 more
core   +1 more source

Singular Value Decomposition (SVD) Berdasarkan Intensitas Pencahayaannya Untuk Pengenal Wajah [PDF]

open access: yesSetrum : 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

Reducing Memory Cost of Exact Diagonalization using Singular Value Decomposition [PDF]

open access: yes, 2011
We present a modified Lanczos algorithm to diagonalize lattice Hamiltonians with dramatically reduced memory requirements, {\em without restricting to variational ansatzes}. The lattice of size $N$ is partitioned into two subclusters.
/SLAC   +5 more
core   +2 more sources

Harmonic detection algorithm based on improved SVD and Prony

open access: yesDianzi 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

Dynamic RBC-To-Membrane Ratio in <sup>129</sup>Xe MRI: A Biomarker of Decreased Lung Function in Pulmonary and Vascular Diseases. [PDF]

open access: yesMagn Reson Med
ABSTRACT Purpose To present a method for quantifying dissolved 129Xe spectroscopy using singular value decomposition (SVD) and a dynamic red blood cell (RBC)/membrane ratio as a biomarker of disease. Methods A spectroscopic sequence was performed in 45 subjects (27 healthy, 12 dyspnea of unknown origin [DUO], and 6 pulmonary hypertension [PH ...
GarcĂ­a Delgado GM   +8 more
europepmc   +2 more sources

A Constructive Algorithm for Decomposing a Tensor into a Finite Sum of Orthonormal Rank-1 Terms [PDF]

open access: yes, 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

Blockwise SVD with error in the operator and application to blind deconvolution [PDF]

open access: yes, 2012
We consider linear inverse problems in a nonparametric statistical framework. Both the signal and the operator are unknown and subject to error measurements.
Delattre, S.   +3 more
core   +3 more sources

Enhancing artificial neural network learning efficiency through Singular value decomposition for solving partial differential equations

open access: yesResults in Applied Mathematics
Partial differential equations (PDEs) hold significant potential for modelling natural phenomena. It is essential to look at a practical way to solve the PDEs.
Alfi Bella Kurniati   +3 more
doaj   +1 more source

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