Analysis of broadband GEVD-based blind source separation
Redif, Soydan and Pestana, Jennifer and Proudler, Ian K.; (2019) Analysis of broadband GEVD-based blind source separation. In: ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, Piscataway, NJ, pp. 8028-8032. ISBN 9781479981311 (https://doi.org/10.1109/ICASSP.2019.8683237)
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Abstract
One approach to blind source separation of instantaneously mixed, non-stationary sources involves using the generalized eigenvalue decomposition of two estimated covariance matrices. The assumption is that the source statistics change with time whilst the mixing matrix does not. A recent generalisation of this approach to convolutive mixtures was achieved by extending the generalized eigenvalue decomposition to polynomial matrices. In this paper, we present a further investigation into this broadband BSS technique. We derive some expressions for the conditions under which source separation is possible. The validity of our analysis is illustrated through some computer simulations.
ORCID iDs
Redif, Soydan, Pestana, Jennifer ORCID: https://orcid.org/0000-0003-1527-3178 and Proudler, Ian K.;-
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Item type: Book Section ID code: 70673 Dates: DateEvent17 April 2019Published17 April 2019Published Online1 March 2019AcceptedNotes: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Subjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Science > Mathematics and Statistics
Strategic Research Themes > Measurement Science and Enabling Technologies
Faculty of Engineering > Electronic and Electrical EngineeringDepositing user: Pure Administrator Date deposited: 02 Dec 2019 11:27 Last modified: 21 Nov 2024 01:29 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/70673