Recurrent networks for separating extractable-target nonlinear mixtures. Part II. Blind configurations

@article{Hosseini2013RecurrentNF,
  title={Recurrent networks for separating extractable-target nonlinear mixtures. Part II. Blind configurations},
  author={Shahram Hosseini and Yannick Deville},
  journal={Signal Processing},
  year={2013},
  volume={93},
  pages={671-683}
}
While most reported blind source separation methods concern linear mixtures, we here address the nonlinear case. In the first part of this paper, we introduced a general class of nonlinear mixtures which can be inverted using recurrent networks. That part was focused on separating structures themselves and therefore on the non-blind configuration, whereas the current paper addresses the estimation of the parameters of this large class of structures in a blind context. We propose a maximum… CONTINUE READING
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