Title :
Number of Sources Uncertainty in Blind Source Separation. Application to EMG Signal Processing
Author :
Snoussi, H. ; Khanna, S. ; Hewson, D. ; Duchene, J.
Author_Institution :
Univ. of Technol. of Troyes, Troyes
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.
Keywords :
Laplace equations; blind source separation; electromyography; medical signal processing; probability; EMG signal processing; Laplace approximation; blind source separation; marginal a posteriori probability maximization; source number uncertainty; wavelet spectral matching separating algorithm; Approximation algorithms; Bayesian methods; Blind source separation; Covariance matrix; Data processing; Electromyography; Signal processing; Signal processing algorithms; Source separation; Uncertainty; Algorithms; Bayes Theorem; Electromyography; Signal Processing, Computer-Assisted; Uncertainty;
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
Print_ISBN :
978-1-4244-0787-3
DOI :
10.1109/IEMBS.2007.4353852
