  In this contribution, we consider the problem of blind source separation in a
Bayesian estimation framework. The wavelet representation allows us to assign
an adequate prior distribution to the wavelet coefficients of the sources. MCMC
algorithms are implemented to test the validity of the proposed approach, and
the non linear approximation of the wavelet transform is exploited to aleviate
the algorithm.
