• DocumentCode
    1544026
  • Title

    Canonical Polyadic Decomposition Based on a Single Mode Blind Source Separation

  • Author

    Zhou, Guoxu ; Cichocki, Andrzej

  • Author_Institution
    Lab. for Adv. Brain Signal Process., RIKEN BSI, Wako, Japan
  • Volume
    19
  • Issue
    8
  • fYear
    2012
  • Firstpage
    523
  • Lastpage
    526
  • Abstract
    A new canonical polyadic (CP) decomposition method is proposed in this letter, where one factor matrix is extracted first by using any standard blind source separation (BSS) method and the remainder components are computed efficiently via sequential singular value decompositions of rank-1 matrices. The new approach provides more interpretable factors and it is extremely efficient for ill-conditioned problems. Especially, it overcomes the bottleneck problems, which often cause very slow convergence speed in CP decompositions. Simulations confirmed the validity and efficiency of the proposed method.
  • Keywords
    blind source separation; matrix algebra; singular value decomposition; canonical polyadic decomposition; rank-1 matrices; sequential singular value decomposition; single mode blind source separation; Blind source separation; Convergence; Matrix decomposition; Signal processing algorithms; Tensile stress; Vectors; Blind source separation; CP (PARAFAC) decompositions; bottleneck problem; tensor decompositions;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2012.2205237
  • Filename
    6220848