Bayesian blind separation of generalized hyperbolic processes in noisy and underdeterminate mixtures

  title={Bayesian blind separation of generalized hyperbolic processes in noisy and underdeterminate mixtures},
  author={Hichem Snoussi and J{\'e}r{\^o}me Idier},
  journal={IEEE Transactions on Signal Processing},
In this paper, we propose a Bayesian sampling solution to the noisy blind separation of generalized hyperbolic signals. Generalized hyperbolic models, introduced by Barndorff-Nielsen in 1977, represent a parametric family able to cover a wide range of real signal distributions. The alternative construction of these distributions as a normal mean variance (continuous) mixture leads to an efficient implementation of the Markov chain Monte Carlo method applied to source separation. The incomplete… CONTINUE READING


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