• 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