Whitening of Background Brain Activity via Parametric Modeling

Kamel, Nidal; Samraj, Andrews; Mousavi, Arash

doi:https://doi.org/10.1155/2007/48720

Discrete Dynamics in Nature and Society

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Research Article | Open Access

Volume 2007 | Article ID 048720 | https://doi.org/10.1155/2007/48720

Whitening of Background Brain Activity via Parametric Modeling

Nidal Kamel,¹Andrews Samraj,²and Arash Mousavi²

Received12 Apr 2007

Accepted10 Jun 2007

Published07 Aug 2007

Abstract

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.

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Copyright

Copyright © 2007 Nidal Kamel et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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