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Dimensionality Reduction in ICA and Rank-(R1,R2,...,RN) Reduction in Multilinear Algebra

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

Abstract

We show that the best rank-(R 1,R 2,...,R N ) approximation in multilinear algebra is a powerful tool for dimensionality reduction in ICA schemes without prewhitening. We consider the application to different classes of ICA algorithms.

Keywords

Dimensionality Reduction Blind Source Separation Matrix Anal Multilinear Algebra Orthogonal Iteration 
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
  • 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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