Whitening of background brain activity via parametric modeling

N., Kamel and A, Samraj and A, Mousavi (2007) Whitening of background brain activity via parametric modeling. DISCRETE DYNAMICS IN NATURE AND SOCIETY (48720 ). ISSN 1026-0226

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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.

Item Type:Article
Impact Factor:Cites in 2009 to articles published in: 2008 = 83 Number of articles published in: 2008 = 58 2007 = 81 2007 = 46 Sum: 164 Sum: 104 Calculation: Cites to recent articles 164 = 1.577 Number of recent articles 104
Uncontrolled Keywords:Mathematics, Interdisciplinary Applications; Multidisciplinary Sciences
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments / MOR / COE:Departments > Electrical & Electronic Engineering
ID Code:2328
Deposited By: Mr Helmi Iskandar Suito
Deposited On:23 Jun 2010 03:38
Last Modified:19 Jan 2017 08:27

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