A Euclidean Direction based algorithm for blind source separation using a natural gradient

Glen W. Mabey, Jacob Gunther, Tamal Bose

Research output: Contribution to journalConference article

1 Scopus citations

Abstract

The development in this paper is a extension of the adaptive RLS-type algorithm proposed by Zhu and Zhang. Their work uses the matrix inversion lemma to iteratively solve the equation obtained from the natural gradient of the nonlinear principle component analysis problem. This paper reduces the complexity of the solution by applying the Euclidean Direction Search concept in place of the matrix inversion lemma. The simulations performed show that the convergence rate is comparable, albeit slower, but with reduced complexity per iteration.

Original languageEnglish (US)
Pages (from-to)V-561-V-564
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume5
StatePublished - Sep 27 2004
Externally publishedYes
EventProceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing - Montreal, Que, Canada
Duration: May 17 2004May 21 2004

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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