Title :
A family of frequency- and time-domain contrasts for blind separation of convolutive mixtures of temporally dependent signals
Author :
Castella, Marc ; Pesquet, Jean-Christophe ; Petropulu, Athina P.
Author_Institution :
Inst. Gaspard Monge, Univ. de Marne-la-Vallee, Marne La Vallee, France
Abstract :
This paper addresses the problem of blind separation of convolutive mixtures via contrast maximization. New frequency domain contrast functions are constructed based on higher order spectra of the observations. They allow to separate mixtures of sources that are spatially independent and temporally possibly nonlinear processes. Using Parseval´s formula, the former criteria yield a general class of time-domain contrasts, which extends to the convolutive case results that have been previously obtained in the context either of instantaneous mixtures or of independent and identically distributed (i.i.d.) sources. A Monte Carlo simulation study is carried out for comparison between the different contrasts, thus providing a guideline about the choice of an appropriate contrast.
Keywords :
Monte Carlo methods; blind source separation; frequency-domain analysis; optimisation; time-domain analysis; Monte Carlo simulation; Parseval formula; blind separation; contrast maximization; convolutive mixture; frequency-domain contrast; higher order spectra; independent and identically distributed sources; temporally dependent signal; time-domain contrast; Biomedical engineering; Biomedical signal processing; Deconvolution; Frequency domain analysis; Guidelines; Higher order statistics; MIMO; Multiaccess communication; Source separation; Time domain analysis;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2004.838938