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OFAI-TR-2001-05 ( 66kB g-zipped PostScript file,  139kB PDF file)

Single Trial Estimation of Evoked Potentials using Gaussian Mixture Models with Integrated Noise Component

Arthur Flexer, Herbert Bauer, Claus Lamm, Georg Dorffner

Gaussian Mixture Models with integrated noise component are a method developed for speech analysis to estimate signals hidden in background noise. We apply this technique to estimate 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 shown to compare favourably to other techniques for single trial estimation.

Keywords: signal processing, mixture models, EEG, noise removal

Citation: Flexer A., Bauer H., Lamm C., Dorffner G.: Single Trial Estimation of Evoked Potentials Using Gaussian Mixture Models with Integrated Noise Component, in Dorffner G., et al.(eds.), Artificial Neural Networks - ICANN 2001, International Conference, Vienna, Austria, Lecture Notes In Computer Science 2130, Springer, pp. 609-616, 2001.