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Warped AR modelling and spectral estimation for EEG signals

Lookup NU author(s): Dr Luis Peraza Rodriguez

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Abstract

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)

Conference Name: 19th Biennial International EURASIP Conference Biosignal

Year of Conference: 2008

Pages: 12-12

Publisher: Brno University of Technology

Library holdings: Search Newcastle University Library for this item

ISBN: 9788021436121


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