A matrix-pencil approach to blind separation of colored nonstationary signals

For many signal sources such as speech with distinct, nonwhite power spectral densities, second-order statistics of the received signal mixture can be exploited for signal separation. Without knowledge of the noise correlation matrix, we propose a simple and yet effective signal extraction method fo...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on signal processing 2000-03, Vol.48 (3), p.900-907
Main Authors: Chunqi Chang, Ding, Zhi, Sze Fong Yau, Chan, F.H.Y.
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Biomedical signal processing
Biosensors
Blind source separation
Blinds
Density
Exact sciences and technology
Frequency
Information, signal and communications theory
Matrices
Noise
Pencils
Reduced order systems
Separation
Signal and communications theory
Signal processing
Signal processing algorithms
Signal, noise
Source separation
Speech processing
Statistics
Telecommunications and information theory
White noise
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:For many signal sources such as speech with distinct, nonwhite power spectral densities, second-order statistics of the received signal mixture can be exploited for signal separation. Without knowledge of the noise correlation matrix, we propose a simple and yet effective signal extraction method for signal source separation under unknown temporally white noise. This new and unbiased signal extractor is derived from the matrix pencil formed between output autocorrelation matrices at different delays. Based on the matrix pencil, an ESPRIT-type algorithm is derived to get an optimal solution in the least square sense. Our method is well suited for systems with colored sensor noises and for nonstationary signals.
ISSN:1053-587X
1941-0476
DOI:10.1109/78.824690