Analysis of broadband GEVD-based blind source separation

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

1 Downloads (Pure)

Abstract

One approach to blind source separation of instantaneously mixed, non-stationary sources involves using the generalized eigenvalue decomposition of two estimated covariance matrices. The assumption is that the source statistics change with time whilst the mixing matrix does not. A recent generalisation of this approach to convolutive mixtures was achieved by extending the generalized eigenvalue decomposition to polynomial matrices. In this paper, we present a further investigation into this broadband BSS technique. We derive some expressions for the conditions under which source separation is possible. The validity of our analysis is illustrated through some computer simulations.
Original languageEnglish
Title of host publicationICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages8028-8032
Number of pages5
ISBN (Electronic)9781479981311
ISBN (Print)9781479981311
DOIs
Publication statusE-pub ahead of print - 17 Apr 2019

Keywords

  • non-stationary
  • broadband
  • blind signal separation
  • generalised eigenvalue decomposition

Fingerprint Dive into the research topics of 'Analysis of broadband GEVD-based blind source separation'. Together they form a unique fingerprint.

  • Cite this

    Redif, S., Pestana, J., & Proudler, I. K. (2019). Analysis of broadband GEVD-based blind source separation. In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 8028-8032). Piscataway, NJ: IEEE. https://doi.org/10.1109/ICASSP.2019.8683237