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A Grassmann-Rayleigh Quotient Iteration for Dimensionality Reduction in ICA

  • Lieven De Lathauwer
  • Luc Hoegaerts
  • Joos Vandewalle
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3195)

Abstract

We derive a Grassmann-Rayleigh Quotient Iteration for the computation of the best rank-(R 1, R 2, R 3) approximation of higher-order tensors. We present some variants that allow for a very efficient estimation of the signal subspace in ICA schemes without prewhitening.

Keywords

Dimensionality Reduction Invariant Subspace Matrix Anal Multilinear Algebra Signal Subspace 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Lieven De Lathauwer
    • 1
    • 2
  • Luc Hoegaerts
    • 2
  • Joos Vandewalle
    • 2
  1. 1.ETIS (CNRS, ENSEA, UCP), UMR 8051Cergy-PontoiseFrance
  2. 2.E.E. Dept. (ESAT) – SCDK.U.LeuvenLeuvenBelgium

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