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Proceedings Paper

New approach for blind source separation using time-frequency distributions
Author(s): Adel Belouchrani; Moeness G. Amin
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Paper Abstract

This paper deals with the problem of blind source separation which consists of recovering a set of signals from instantaneous linear mixture of them. So far, this problem has been solved using statistical information available on the source signals. Here, we propose an approach for blind source separation based on time-frequency (t-f) signal representations. This approach is based on a `joint diagonalization' of a combined set of time frequency distribution matrices which correspond to different t-f points. It relies on the difference in the t-f signatures of the sources to be separated. In contrast to existing techniques, the proposed approach allows the separation of Gaussian sources with identical spectra shape. Because of changes incurred in the t-f signal structures due to time- delay, the new approach can be employed to separate multipath signals received by multi-sensor array. Moreover, the effects of spreading the noise power while localizing the source energy in the time frequency domain amounts to increasing the signal to noise ratio and hence improved performance. Numerical examples are provided to illustrate the effectiveness of our method.

Paper Details

Date Published: 22 October 1996
PDF: 11 pages
Proc. SPIE 2846, Advanced Signal Processing Algorithms, Architectures, and Implementations VI, (22 October 1996); doi: 10.1117/12.255434
Show Author Affiliations
Adel Belouchrani, Villanova Univ. (United States)
Moeness G. Amin, Villanova Univ. (United States)

Published in SPIE Proceedings Vol. 2846:
Advanced Signal Processing Algorithms, Architectures, and Implementations VI
Franklin T. Luk, Editor(s)

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