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Warped AR modelling and spectral estimation for EEG signals

Lookup NU author(s): Dr Luis Peraza RodriguezORCiD



This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by Brno University of Technology, 2008.

For re-use rights please refer to the publisher's terms and conditions.


Warped autoregressive (WAR) models are proposed for the obtention of reduced order and high quality power spectral density estimators for EEG signals. The use of WAR-based versus linear AR-based PSD estimators allowed comparable quality estimates in the alpha band with considerably less number of coefficients when applied to real EEG data. WAR-based models may improve the performance of quantitative EEG algorithms while decreasing their computational load, complexity, and memory requirements.

Publication metadata

Author(s): Peraza LR, Bouchereau F

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 19th Biennial International EURASIP Conference Biosignal (BIOSIGNAL 2008)

Year of Conference: 2008

Pages: 12-12

Online publication date: 29/06/2008

Date deposited: 07/12/2012

ISSN: 1211-412X

Publisher: Brno University of Technology

Library holdings: Search Newcastle University Library for this item

ISBN: 9788021436121