  The destriping technique is a viable tool for removing different kinds of
systematic effects in CMB related experiments. It has already been proven to
work for gain instabilities that produce the so-called 1/f noise and periodic
fluctuations due to e.g. thermal instability. Both effects when coupled with
the observing strategy result in stripes on the observed sky region. Here we
present a maximum-likelihood approach to this type of technique and provide
also a useful generalization. As a working case we consider a data set similar
to what the Planck satellite will produce in its Low Frequency Instrument
(LFI). We compare our method to those presented in the literature and find some
improvement in performance. Our approach is also more general and allows for
different base functions to be used when fitting the systematic effect under
consideration. We study the effect of increasing the number of these base
functions on the quality of signal cleaning and reconstruction. This study is
related to Planck LFI activities.
