  We present a method for the analysis of electroencephalograms (EEG).
  In particular, small signals due to stimulation, so called evoked potentials,
have to be detected in the background EEG. This is achieved by using a
denoising implementation based on the wavelet decomposition. One recording of
visual evoked potentials, and recordings of auditory evoked potentials from 4
subjects corresponding to different age groups are analyzed. We find higher
variability in older individuals. Moreover, since the evoked potentials are
identified at the single stimulus level (without need of ensemble averaging),
this will allow the calculation of better resolved averages. Since the method
is parameter free (i.e. it does not need to be adapted to the particular
characteristics of each recording), implementations in clinical settings are
imaginable.
