What is it about?
Introduces a method for separating convolutively mixed signals with minimal information about the sources or mixing process. The proposed technique performs blind source separation (BSS) of broadband (convolutive) signals using only second-order statistics.
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Why is it important?
Apart from presenting a new method of solving the broadband blind source separation (BSS) problem, the paper paves the way to further research on the new polynomial GEVD (PGEVD), especially on its applicability to broadband extensions of narrowband problems, traditionally addressed by the regular GEVD.
Perspectives
The paper presents another great example of the importance and applicability of polynomial matrix decompositions.
Dr Soydan Redif
European University of Lefke
Read the Original
This page is a summary of: Convolutive Blind Signal Separation via Polynomial Matrix Generalized Eigenvalue Decomposition , Electronics Letters, November 2016, the Institution of Engineering and Technology (the IET),
DOI: 10.1049/el.2016.3200.
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