DocumentCode :
3846757
Title :
The Higher-Order Singular Value Decomposition: Theory and an Application [Lecture Notes]
Author :
G. Bergqvist;Erik G. Larsson
Author_Institution :
Department of Mathematics Linkoping University SE-58183 Linkoping Sweden
Volume :
27
Issue :
3
fYear :
2010
Firstpage :
151
Lastpage :
154
Abstract :
Tensor modeling and algorithms for computing various tensor decompositions (the Tucker/HOSVD and CP decompositions, as discussed here, most notably) constitute a very active research area in mathematics. Most of this research has been driven by applications. There is also much software available, including MATLAB toolboxes [4]. The objective of this lecture has been to provide an accessible introduction to state of the art in the field, written for a signal processing audience. We believe that there is good potential to find further applications of tensor modeling techniques in the signal processing field.
Keywords :
"Singular value decomposition","Data compression","Testing","Computational efficiency","Tensile stress","Eigenvalues and eigenfunctions","Matrix decomposition","Signal processing algorithms","Noise reduction","Statistics"
Journal_Title :
IEEE Signal Processing Magazine
Publisher :
ieee
ISSN :
1053-5888
Type :
jour
DOI :
10.1109/MSP.2010.936030
Filename :
5447070
Link To Document :
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