文章基本信息

标题：Whitening of Background Brain Activity via Parametric Modeling
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作者：Nidal Kamel ; Andrews Samraj ; Arash Mousavi 等
期刊名称：Discrete Dynamics in Nature and Society
印刷版ISSN：1026-0226
电子版ISSN：1607-887X
出版年度：2007
卷号：2007
DOI：10.1155/2007/48720
出版社：Hindawi Publishing Corporation
摘要：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.