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On the use of joint diagonalization in blind signal processing

  • University of Regensburg
  • Dept. of Electronic and Control Systems Engineering
  • Shimane Medical University

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

24 Zitate (Scopus)

Abstract

Blind source separation (BSS) tries to decompose a given multivariate data set into the product of a mixing matrix and a source vector, both of which are unknown. The sources can be recovered if we pose additional constraints to this model. One class of BSS algorithms is given by algebraic BSS, which recovers the mixing structure by jointly diagonalizing various source condition matrices corresponding to different source models. We review classical BSS algorithms such as FOBI, JADE, AMUSE, SOBI, TDSEP and SONS within this framework; combination of the respective source conditions can then yield additional algorithms as implemented e.g. by JADETD. Extensions to dependent component analysis models such as spatiotemporal or multidimensional BSS are discussed.

OriginalspracheEnglisch
TitelISCAS 2006
Untertitel2006 IEEE International Symposium on Circuits and Systems, Proceedings
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten3586-3589
Seitenumfang4
ISBN (Print)0780393902, 9780780393905
DOIs
PublikationsstatusVeröffentlicht - 2006
Extern publiziertJa
Veranstaltung2006 IEEE International Symposium on Circuits and Systems, ISCAS 2006 - Kos, Griechenland
Dauer: 21 Mai 200624 Mai 2006

Publikationsreihe

NameProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)0271-4310

Konferenz

Konferenz2006 IEEE International Symposium on Circuits and Systems, ISCAS 2006
Land/GebietGriechenland
OrtKos
Zeitraum21/05/0624/05/06

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