Canonical Polyadic Decomposition Based on a Single Mode Blind Source Separation

Guoxu Zhou, Andrzej Cichocki

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)523-526
Number of pages4
JournalIEEE Signal Processing Letters
Volume19
Issue number8
DOIs
Publication statusPublished - Aug 2012
Externally publishedYes

Keywords

  • Blind source separation
  • bottleneck problem
  • CP (PARAFAC) decompositions
  • tensor decompositions

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