Blind Unitary Prewhitening with a Real-Valued Eigendecomposition |
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Authors: | Sergiy A Vorobyov |
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Affiliation: | (1) Department of Communication Systems, Institute of Telecommunications, Darmstadt University of Technology, Merckstr. 25, 64283, Darmstadt, Germany |
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Abstract: | Prewhitening is a standard step for the processing of noisy signals. Typically, eigenvalue decomposition (EVD) of the sample
data covariance matrix is used to calculate the whitening matrix. From a computational point of view, an important problem
here is to reduce the complexity of the EVD of the complex-valued sample data covariance matrix. In this paper, we show that
the computational complexity of the prewhitening step for complex-valued signals can be reduced approximately by a factor
of four when the real-valued EVD is used instead of the complex-valued one. Such complexity reduction can be achieved for
any axis-symmetric array. The performance of the proposed procedure is studied in application to a blind source separation
(BSS) problem. For this application, the performance of the proposed prewhitening scheme is illustrated by means of simulations,
and compared with the conventional prewhitening scheme. Among a number of BSS methods which use prewhitening, the second-order
blind identification procedure has been adopted in this paper. |
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Keywords: | |
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