Blind Source Separation in the Time-Frequency Domain Based on Multiple Hypothesis Testing

Authors:
L. Cirillo;A. Zoubir;M. Amin
Affiliations:
Signal Process. Group, Darmstadt Univ. of Technol., Darmstadt;-;-
Venue:
IEEE Transactions on Signal Processing
Year:
2008

Citing 0
Cited 2

Blind identification of multi-channel systems with single input and unknown orders

Signal Processing
Blind source separation based on high-resolution time-frequency distributions

Computers and Electrical Engineering

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Abstract

This paper considers a time-frequency (t-f)-based approach for blind separation of nonstationary signals. In particular, we propose a time-frequency "point selection" algorithm based on multiple hypothesis testing, which allows automatic selection of auto- or cross-source locations in the time-frequency plane. The selected t-f points are then used via a joint diagonalization and off-diagonalization algorithm to perform source separation. The proposed algorithm is developed assuming deterministic signals with additive white complex Gaussian noise. A performance comparison of the proposed and existing approaches is provided.