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Your query term was 'number = 2001-10'
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OFAI-TR-2001-10 ( 61kB g-zipped PostScript file,  195kB PDF file)

Model-based noise reduction for single trial evoked potentials

Arthur Flexer, Herbert Bauer, Claus Lamm, Georg Dorffner

Two model-based techniques, Gaussian Mixture Models with integrated noise component and Principal Component Analysis, are applied to noise reduction for single trial evoked potentials which are buried in noise up to five times stronger than the signal. An empirical study using artificial data is presented and results are compared to the standard technique of averaging.

Keywords: Gaussian mixture models, Principal Component Analysis, Denoising, EEG

Citation: Flexer A., Bauer H., Lamm C., Dorffner G.: Model-based Noise Reduction for Single Trial Evoked Potentials, in Miller D.J., et al.(eds.), Neural Networks for Signal Processing XI, Institute of Electrical and Electronics Engineers, Inc., New York, NY, pp.499-508, 2001.