  We consider the problem of adaptive blind separation of two sources from
their instantaneous mixtures. We focus on the case where the two sources are
not necessarily independent. By analyzing a general form of adaptive algorithms
we show that separation is possible not only for independent sources but also
for sources that are dependent provided their joint pdf satisfies certain
symmetry conditions. A very interesting problem consists in identifying the
class of dependent sources that are non-separable, namely, the counterpart of
Gaussian sources of the independent case. We corroborate our theoretical
analysis with a number of simulations and give examples of dependent sources
that can be easily separated.
