Results 71 to 80 of about 71,463 (232)

An Aggregative High-Order Singular Value Decomposition Method in Edge Computing

IEEE Access, 2020
In edge computing, for dimensionality reduction and core data extraction, both edge computing node (ECN) and cloud server may implement a high-order singular value decomposition (HOSVD) algorithm before data are passed to local computing models. However,
Junhua Chen, Ping Wang, Chenggen Pu, Qingqing Huang   +3 more
doaj   +1 more source

Sunshine Duration in Brazil From Meteosat (1983–2020): Climatology, Variability and Long‐Term Trends

International Journal of Climatology, EarlyView.
Using nearly four decades of Meteosat satellite data (1983–2020), this study presents a country‐wide climatology of sunshine duration (SDU) in Brazil. The results reveal marked regional contrasts, dominant modes of variability, and significant long‐term trends, providing new information on the most relevant meteorological systems that influence SDU and
Maria Lívia Lins Mattos Gava, Simone Marilene Sievert da Costa, Íris Paraguay Silva   +2 more
wiley   +1 more source

Transformation of Non-Euclidean Space to Euclidean Space for Efficient Learning of Singular Vectors

IEEE Access, 2020
Singular value decomposition (SVD) is a popular technique to extract essential information by reducing the dimension of a feature set. SVD is able to analyze a vast matrix in spite of a relatively low computational cost.
Seunghyun Lee, Byung Cheol Song
doaj   +1 more source

Frozen Differential Scattering in Reconfigurable Complex Media

Laser &Photonics Reviews, EarlyView.
A localized perturbation universally results in a rank‐one update of the scattering matrix of any complex medium. The resulting differential output wavefront is “frozen”: its spatial pattern is fixed (agnostic to the input wavefront). Experiments with a programmable‐metasurface‐parametrized wireless link validate frozen differential scattering and ...
Philipp del Hougne
wiley   +1 more source

Comparative Study of SVD and QRS in Closed-Loop Beamforming Systems

, 2008
We compare two closed-loop beamforming algorithms, one based on singular value decomposition (SVD) and the other based on equal diagonal QR decomposition (QRS).
Sun, Sumei, Yuen, Chau, Zhang, Jian-Kang
core   +1 more source

N-Dimensional Principal Component Analysis [PDF]

, 2010
In this paper, we first briefly introduce the multidimensional Principal Component Analysis (PCA) techniques, and then amend our previous N-dimensional PCA (ND-PCA) scheme by introducing multidirectional decomposition into ND-PCA implementation.
Yu, Hongchuan
core  

Simulation‐Informed Evaluation of Microvascular Parameter Mapping for Diffusion MR Imaging of Solid Tumours

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose We aim to inform the design of new diffusion MRI (dMRI) approaches for microvasculature quantification that enhance the biological specificity of imaging towards cancer. Methods We adopted simulation‐informed modelling of the vascular dMRI signal. We synthesised signals from 1500 synthetic vascular networks, for a variety of protocols (
Anna Kira Voronova, Olivia Prior, Athanasios Grigoriou, Francesc Salvà, Elena Elez, Luz M. Atlagich, Roser Sala‐Llonch, Marco Palombo, Els Fieremans, Dmitry S. Novikov, Raquel Perez‐Lopez, Francesco Grussu   +11 more
wiley   +1 more source

Unraveling complexity: Singular value decomposition in complex experimental data analysis

SciPost Physics Core
Analyzing complex experimental data with multiple parameters is challenging. We propose using Singular Value Decomposition (SVD) as an effective solution.
Judith F. Stein, Aviad Frydman, Richard Berkovits
doaj   +1 more source

Application of SVM and SVD Technique Based on EMD to the Fault Diagnosis of the Rotating Machinery

Shock and Vibration, 2009
Targeting the characteristics that periodic impulses usually occur whilst the rotating machinery exhibits local faults and the limitations of singular value decomposition (SVD) techniques, the SVD technique based on empirical mode decomposition (EMD) is ...
Junsheng Cheng, Dejie Yu, Jiashi Tang, Yu Yang   +3 more
doaj   +1 more source

Enhanced 2D Spiral Cine DENSE MRI Using Low‐Rank Denoising for Improved Apparent Signal‐to‐Noise Ratio, Spatial Resolution, Efficiency, Accuracy, and Accessibility

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To develop a denoising technique for displacement encoding with stimulated echoes (DENSE) MRI that improves spatial resolution, efficiency, and accuracy, and enhances accessibility by implementing DENSE MRI at 0.55 T. Methods We developed a low‐rank denoising technique, which leverages multidimensional spiral cine DENSE MRI data for ...
Shu‐Fu Shih, Yuxiao Wu, Siyue Li, Zhengyang Ming, Arutyun Pogosyan, Fei Han, Holden H. Wu, J. Paul Finn, Kim‐Lien Nguyen, Xiaodong Zhong   +9 more
wiley   +1 more source