title: Number of sources uncertainty in blind source separation. Application to EMG signal processing.
abstract: This contribution deals with the number of components uncertainty in blind source separation. The number of components is estimated by maximizing its marginal a posteriori probability which favors the simplest explanation of the observed data. Marginalizing (integrating over all the parameters) is implemented through the Laplace approximation based on an efficient wavelet spectral matching separating algorithm. The effectiveness of the proposed method is shown on EMG data processing.
authors.affiliation: ICD/LM2S, University of Technology of Troyes, 12, rue Marie Curie, 10000, France. hichem.snoussi@utt.fr
authors.forename: Hichem
authors.initials: H
authors.lastname: Snoussi
authors.forename: Saurabh
authors.initials: S
authors.lastname: Khanna
authors.forename: David
authors.initials: D
authors.lastname: Hewson
authors.forename: Jacques
authors.initials: J
authors.lastname: Duchene
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D004576:Electromyography; D012815:Signal Processing, Computer-Assisted; D035501:Uncertainty