Abstract
Real valued blind source extraction based on a linear predictor is extended to the complex domain using recent advances in complex domain statistics. It is shown that, in general, the mean square prediction error of the algorithm depends both on the covariance matrix and the pseudo-covar-iance matrix of the source signals. To fully utilise the available information, it is thus natural to adopt a widely linear predictor to extract the latent sources from the observed mixture. This way, we derive a new algorithm for the extraction of general complex signals and provide simulation results using benchmark complex data.
Original language | English |
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Title of host publication | 2009 IEEE/SP 15th Workshop on Statistical Signal Processing, SSP '09 |
Pages | 501-504 |
Number of pages | 4 |
DOIs | |
Publication status | Published - 2009 |
Externally published | Yes |
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Applied Mathematics
- Signal Processing
- Computer Science Applications