NMF with Sparse Regularizations in Transformed Domains

@article{Rapin2014NMFWS,
  title={NMF with Sparse Regularizations in Transformed Domains},
  author={J. Rapin and J. Bobin and A. Larue and Jean-Luc Starck},
  journal={SIAM J. Imaging Sci.},
  year={2014},
  volume={7},
  pages={2020-2047}
}
Nonnegative blind source separation, which is also referred to as nonnegative matrix factorization (NMF), is a very active field in domains as different as astrophysics, audio processing, and biomedical signal processing. In this context, the efficient retrieval of the sources requires the use of signal priors such as sparsity. Although NMF has been well studied with sparse constraints in the direct domain, only very few algorithms can encompass nonnegativity together with sparsity in a… Expand

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