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