Single trial estimation of evoked potentials using Gaussian mixture models with integrated noise component

Abstract

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 compared to the standard technique of averaging.