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.
| Original language | English |
|---|---|
| Pages (from-to) | 107-120 |
| Number of pages | 14 |
| Journal | IEEE Transactions on Signal Processing |
| Volume | 53 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Jan 2005 |
| Externally published | Yes |
Keywords
- Blind source separation
- Convolutive mixture
- Deconvolution
- Higher order statistics
- MIMO systems
- Multiuser communications