Evoked response data in electroencephalography (EEG) has typically very low
signal-to-noise ratio, the presence and character of the response to a stimulus
is often obscured by background noise.
Detecting a weak signal of interest on a cluttered background is a problem that
arises also e.g. in radar signal processing.
We present a maximum-likelihood based algorithm for reducing the effects
of spatially colored noise in evoked response EEG data.
Similar signal and noise models have been used in radar detection problem.