MULTIREFERENCE ADAPTIVE NOISE CANCELING APPLIED TO THE EEG

The technique of multireference adaptive noise canceling (MRANC) is ap plied to enhance transient nonstationarities in the electroencephalogr am (EEG), with the adaptation implemented by means of a multilayer-per ceptron artificial neural network (ANN). The method was applied to rec orded EEG segments and the performance on documented nonstationarities recorded. The results show that the neural network (nonlinear) gives an improvement in performance (i.e., signal-to-noise ratio (SNR) of th e nonstationarities) compared to a linear implementation of MRANC. In both cases an improvement in the SNR was obtained. The advantage of th e spatial filtering aspect of MRANC is highlighted when the performanc e of MRANC is compared to that of the inverse auto-regressive filterin g of the EEG, a purely temporal filter.