TUTCRIS - Tampereen teknillinen yliopisto


Lévy NMF : un modèle robuste de séparation de sources non-négatives



OtsikkoActes du XXVIème Colloque GRETSI
TilaJulkaistu - 5 syyskuuta 2017
OKM-julkaisutyyppiD3 Artikkeli ammatillisessa konferenssijulkaisussa
TapahtumaGRETSI conference -
Kesto: 5 syyskuuta 20178 syyskuuta 2017


ConferenceGRETSI conference


In this paper, we address the problem of robust source separation of nonnegative data. We introduce the PαS distributions, which are a subclass of the stable distributions family, to model the nonnegative latent sources. Since those distributions are heavy-tailed, they are expected to be robust to outliers. Considering the Lévy distribution, the only PαS distribution whose density admits a closed form expression, we propose a mixture model called Lévy Nonnegative Matrix Factorization (Lévy NMF). The model is estimated in a maximum-likelihood sense. We also derive an estimator of the sources which extends the validity of the generalized Wiener filtering to the PαS case. Experiments on musical spectrograms and fluorescence spectra highlight the potential of the Lévy NMF model for decomposing nonnegative data.