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Abstract: We present an efficient algorithm for the blind signal separation (BSS) problem with convolutive signal mixtures, as it usually appears in Acoustics, e.g., in the cocktail party problem. Since acoustical signals are typically non-stationary and non-white, we make use of these two statistical properties in the formulation of the blind cost function. In order to achieve true signal separation, the algorithm aims at finding a single polynomial matrix, the convolutive separation matrix, that... (Update)
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BibTeX entry: (Update)
@misc{ joho-convolutive,
author = "Marcel Joho",
title = "Convolutive Blind Signal Separation in Acoustics by Joint Approximate Diagonalization
of Spatiotemporal Correlation Matrices",
url = "citeseer.ist.psu.edu/joho04convolutive.html" }
Citations (may not include all citations):461 Nonlinear Programming (context) - Bertsekas - 1999
356 Multirate Systems and Filter Banks (context) - Vaidyanathan - 1993
57 Introductory Functional Analysis with Applications (context) - Kreyszig - 1978
35 Jacobi angles for simultaneous diagonalization - Cardoso, Souloumiac - 1996
30 Convolutive blind separation of nonstationary sources - Parra, Spence - 2000
5 A systematic approach to adaptive algorithms for multichanne.. (context) - Joho - 2000
3 A generalization of blind source separation algorithms for c.. (context) - Buchner, Aichner et al.
2 Optimisation algorithms exploiting unitary constraints (context) - Manton - 2002
2 Minimal distortion principle for blind source separation (context) - Matsuoka, Nakashima - 2001
1 Algorithms on the Stiefel manifold for joint diagonalisation (context) - Nikpour, Manton et al. - 2002
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