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  • In this article we propose a computationally efficient method (termed FCOMBI) to combine the strengths of non-Gaussianity based blind source separation (BSS) and cross-correlation-based BSS. This is done by fusing the separtion abilities of two well known algorithms: EFICA and WASOBI. The algorithm is suitable for the analysis of very high-dimensional datasets like high-density Electroencephalogram or Magnetoencephalogram recordings.
  • In this article we propose a computationally efficient method (termed FCOMBI) to combine the strengths of non-Gaussianity based blind source separation (BSS) and cross-correlation-based BSS. This is done by fusing the separtion abilities of two well known algorithms: EFICA and WASOBI. The algorithm is suitable for the analysis of very high-dimensional datasets like high-density Electroencephalogram or Magnetoencephalogram recordings. (en)
  • V clanku je navrzen vypocetne nenarocny algoritmus, ktery kombinuje schopnosti slepe separace dvou odlisnych algorimu: EFICA, ktery vyuziva ne-gaussovskosti rozlozeni jednotlivych separovanych zdroju, a WASOBI, ktery vyuziva rozdilnosti frekvencnich spekter jednotlivych zdroju. Algoritmus je vhodny pro analyzu mnohadimensionalnich dat z elektroencefalogramu a magnetoencefaloogramu s vysokym rozlisenim. (cs)
Title
  • A fast algorithm for blind separation of non-Gaussian and time-correlated signals
  • A fast algorithm for blind separation of non-Gaussian and time-correlated signals (en)
  • Rychlý algoritmus pro slepou separaci ne-Gaussovských a časově korelovaných signálů (cs)
skos:prefLabel
  • A fast algorithm for blind separation of non-Gaussian and time-correlated signals
  • A fast algorithm for blind separation of non-Gaussian and time-correlated signals (en)
  • Rychlý algoritmus pro slepou separaci ne-Gaussovských a časově korelovaných signálů (cs)
skos:notation
  • RIV/67985556:_____/07:00085969!RIV08-AV0-67985556
http://linked.open.../vavai/riv/strany
  • 1731;1735
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1M0572), P(GA102/05/0278), P(GP102/07/P384), Z(AV0Z10750506)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 407884
http://linked.open...ai/riv/idVysledku
  • RIV/67985556:_____/07:00085969
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Blind source separation; multidimensional independent components; FCOMBI (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [726361697675]
http://linked.open...v/mistoKonaniAkce
  • Poznan
http://linked.open...i/riv/mistoVydani
  • Poznan
http://linked.open...i/riv/nazevZdroje
  • Proccedings of the 15th European Signal Processing Conference. EUSIPCO 2007
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Koldovský, Zbyněk
  • Tichavský, Petr
  • Gómez-Herrero, G.
  • Egiazarian, K.
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • PTETiS
https://schema.org/isbn
  • 978-83-921340-2-2
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