matrix decompositions
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scholarly journals Low-rank matrix decompositions for ab initio nuclear structure

2021 ◽  
pp. 136623
Author(s):  
A. Tichai ◽  
P. Arthuis ◽  
K. Hebeler ◽  
M. Heinz ◽  
J. Hoppe ◽  
...  
Keyword(s):  
Ab Initio ◽  
Nuclear Structure ◽  
Low Rank ◽  
Matrix Decompositions ◽  
Rank Matrix ◽  
Low Rank Matrix

Polarimetry of soil and vegetation in the visible II: Mueller matrix decompositions

2021 ◽  
pp. 107622
Author(s):  
Sergey N. Savenkov ◽  
Alexander A. Kohkanovsky ◽  
Evgen A. Oberemok ◽  
Ivan S. Kolomiets ◽  
Alexander S. Klimov
Keyword(s):  
Mueller Matrix ◽  
Matrix Decompositions

scholarly journals Truncated singular value decomposition in ripped photo recovery

2021 ◽  
Vol 36 ◽  
pp. 04008
Author(s):  
Kong Hoong Lem
Keyword(s):  
Singular Value Decomposition ◽  
Linear Algebra ◽  
Singular Value ◽  
Frobenius Norm ◽  
Truncated Singular Value Decomposition ◽  
Matrix Decompositions ◽  
Truncated Svd ◽  
Value Decomposition

Singular value decomposition (SVD) is one of the most useful matrix decompositions in linear algebra. Here, a novel application of SVD in recovering ripped photos was exploited. Recovery was done by applying truncated SVD iteratively. Performance was evaluated using the Frobenius norm. Results from a few experimental photos were decent.

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