Singular value decomposition of noisy data: mode corruption

2019 ◽  
Vol 60 (8) ◽  
Author(s):  
Brenden P. Epps ◽  
Eric M. Krivitzky
Keyword(s):  
Singular Value Decomposition ◽  
Noisy Data ◽  
Singular Value ◽  
Value Decomposition

Indexing of powder diffraction patterns by iterative use of singular value decomposition

2003 ◽  
Vol 36 (1) ◽  
pp. 86-95 ◽  
Author(s):  
A. A. Coelho
Keyword(s):  
Singular Value Decomposition ◽  
Powder Diffraction ◽  
Present Method ◽  
Linear Equations ◽  
Noisy Data ◽  
Simulated Data ◽  
Singular Value ◽  
Fast Method ◽  
Diffraction Patterns ◽  
Value Decomposition

A fast method for indexing powder diffraction patterns has been developed for large and small lattices of all symmetries. The method is relatively insensitive to impurity peaks and missing highd-spacings: on simulated data, little effect in terms of successful indexing has been observed when one in threed-spacings are randomly removed. Comparison with three of the most popular indexing programs, namelyITO,DICVOL91andTREOR90, has shown that the present method as implemented in the programTOPASis more successful at indexing simulated data. Also significant is that the present method performs well on typically noisy data with large diffractometer zero errors. Critical to its success, the present method uses singular value decomposition in an iterative manner for solving linear equations relatinghklvalues tod-spacings.

Improving TF-IDF with Singular Value Decomposition (SVD) for Feature Extraction on Twitter

2017 ◽  
Author(s):  
Ammar Ismael Kadhim ◽  
Yu-N Cheah ◽  
Inaam Abbas Hieder ◽  
Rawaa Ahmed Ali
Keyword(s):  
Feature Extraction ◽  
Singular Value Decomposition ◽  
Singular Value ◽  
Value Decomposition

Multi-scale singular value decomposition polarization image fusion defogging algorithm and experiment

2020 ◽  
Vol 13 (6) ◽  
pp. 1-10
Author(s):  
ZHOU Wen-zhou ◽  
◽  
FAN Chen ◽  
HU Xiao-ping ◽  
HE Xiao-feng ◽  
...  
Keyword(s):  
Singular Value Decomposition ◽  
Image Fusion ◽  
Singular Value ◽  
Multi Scale ◽  
Polarization Image ◽  
Value Decomposition
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