Whitening of Background Brain Activity via Parametric Modeling

Several signal subspace techniques have been recently suggested for the extraction of the visual evoked potential signals from brain background colored noise. The majority of these techniques assume the background noise as white, and for colored noise, it is suggested to be whitened, without further...

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Main Authors: Kamel, Nidal, Samraj, Andrews, Mousavi, Arash
Format: Article
Language:English
Published: HINDAWI PUBLISHING CORPORATION 2007
Subjects:
Online Access:http://shdl.mmu.edu.my/3152/
http://shdl.mmu.edu.my/3152/1/1166.pdf
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author Kamel, Nidal
Samraj, Andrews
Mousavi, Arash
author_facet Kamel, Nidal
Samraj, Andrews
Mousavi, Arash
author_sort Kamel, Nidal
building MMU Institutional Repository
collection Online Access
description Several signal subspace techniques have been recently suggested for the extraction of the visual evoked potential signals from brain background colored noise. The majority of these techniques assume the background noise as white, and for colored noise, it is suggested to be whitened, without further elaboration on how this might be done. In this paper, we investigate the whitening capabilities of two parametric techniques: a direct one based on Levinson solution of Yule-Walker equations, called AR Yule-Walker, and an indirect one based on the least-squares solution of forward-backward linear prediction ( FBLP) equations, called AR-FBLP. The whitening effect of the two algorithms is investigated with real background electroencephalogram ( EEG) colored noise and compared in time and frequency domains. Copyright (C) 2007.
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spelling mmu-31522014-03-03T04:35:09Z http://shdl.mmu.edu.my/3152/ Whitening of Background Brain Activity via Parametric Modeling Kamel, Nidal Samraj, Andrews Mousavi, Arash T Technology (General) QA75.5-76.95 Electronic computers. Computer science Several signal subspace techniques have been recently suggested for the extraction of the visual evoked potential signals from brain background colored noise. The majority of these techniques assume the background noise as white, and for colored noise, it is suggested to be whitened, without further elaboration on how this might be done. In this paper, we investigate the whitening capabilities of two parametric techniques: a direct one based on Levinson solution of Yule-Walker equations, called AR Yule-Walker, and an indirect one based on the least-squares solution of forward-backward linear prediction ( FBLP) equations, called AR-FBLP. The whitening effect of the two algorithms is investigated with real background electroencephalogram ( EEG) colored noise and compared in time and frequency domains. Copyright (C) 2007. HINDAWI PUBLISHING CORPORATION 2007 Article NonPeerReviewed text en http://shdl.mmu.edu.my/3152/1/1166.pdf Kamel, Nidal and Samraj, Andrews and Mousavi, Arash (2007) Whitening of Background Brain Activity via Parametric Modeling. Discrete Dynamics in Nature and Society, 2007. p. 1. ISSN 1026-0226 http://dx.doi.org/10.1155/2007/48720 doi:10.1155/2007/48720 doi:10.1155/2007/48720
spellingShingle T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
Kamel, Nidal
Samraj, Andrews
Mousavi, Arash
Whitening of Background Brain Activity via Parametric Modeling
title Whitening of Background Brain Activity via Parametric Modeling
title_full Whitening of Background Brain Activity via Parametric Modeling
title_fullStr Whitening of Background Brain Activity via Parametric Modeling
title_full_unstemmed Whitening of Background Brain Activity via Parametric Modeling
title_short Whitening of Background Brain Activity via Parametric Modeling
title_sort whitening of background brain activity via parametric modeling
topic T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
url http://shdl.mmu.edu.my/3152/
http://shdl.mmu.edu.my/3152/
http://shdl.mmu.edu.my/3152/
http://shdl.mmu.edu.my/3152/1/1166.pdf