Separation of delayed parameterized sources

Hassan Mortada (1) , Vincent Mazet (1) , Charles Soussen (2) , Christophe Collet (1)

1 ICube - Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie
2 CRAN - Centre de Recherche en Automatique de Nancy

This paper addresses the delayed (or anechoic) source separation problem in the case of parameterized deterministic sources. An alternating least square scheme is proposed to estimate the source parameters, the mixing coefficients and the delays. For the challenging delay parameter we adapt a sparse approximation strategy. A first algorithm considers discrete delays; then an extension, inspired by the recent sparse deconvolution literature, allows for continuous delay estimation. Numerical simulations demonstrate the effectiveness of the proposed algorithms compared to state-of-the-art methods for highly correlated Gaussian sources.

Mots clés: anechoic source separation; alternating least squares; continuous delay estimation; decomposition of spectroscopic signals; correlated sources

Domaines: Traitement du signal et de l'image [eess.SP]

Hassan Mortada, Vincent Mazet, Charles Soussen, Christophe Collet. Separation of delayed parameterized sources. 25th European Signal Processing Conference, EUSIPCO 2017, Aug 2017, Kos Island, Greece. ⟨hal-01497248v2⟩