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Blind Source Separation Using Time-Frequency Masking

Mohammed, Abbas ; Ballal, Tariq and Grbic, Nedelko LU (2007) In Radioengineering 16(4). p.96-100
Abstract
In blind source separation (BSS), multiple mixtures acquired by an array of sensors are processed in order to recover the initial multiple source signals. While a variety of Independent Component Analysis (ICA)-based techniques are being used, in this paper we used a newly proposed method: The Degenerate Unmixing and Estimation Technique (DUET). The method applies when sources are W-disjoint orthogonal; that is, when the time-frequency representations, of any two signals in the mixtures are disjoint sets. The method uses an online algorithm to perform gradient search for the mixing parameters, and simultaneously construct binary time-frequency masks that are used to partition one of the mixtures to recover the original source signals.... (More)
In blind source separation (BSS), multiple mixtures acquired by an array of sensors are processed in order to recover the initial multiple source signals. While a variety of Independent Component Analysis (ICA)-based techniques are being used, in this paper we used a newly proposed method: The Degenerate Unmixing and Estimation Technique (DUET). The method applies when sources are W-disjoint orthogonal; that is, when the time-frequency representations, of any two signals in the mixtures are disjoint sets. The method uses an online algorithm to perform gradient search for the mixing parameters, and simultaneously construct binary time-frequency masks that are used to partition one of the mixtures to recover the original source signals. Previous studies have demonstrated the robustness of the method. However, the investigation in this paper reveals significant drawbacks associated with the technique which should be addressed in the future. (Less)
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author
; and
publishing date
type
Contribution to journal
publication status
published
subject
in
Radioengineering
volume
16
issue
4
article number
4
pages
5 pages
publisher
Czech Technical University
external identifiers
  • scopus:80053009261
ISSN
1210-2512
language
English
LU publication?
no
id
91e260ad-8e0b-4424-960c-d4cae5665d10
alternative location
http://hdl.handle.net/11012/57331
date added to LUP
2016-06-23 14:22:21
date last changed
2022-04-01 00:56:15
@article{91e260ad-8e0b-4424-960c-d4cae5665d10,
  abstract     = {{In blind source separation (BSS), multiple mixtures acquired by an array of sensors are processed in order to recover the initial multiple source signals. While a variety of Independent Component Analysis (ICA)-based techniques are being used, in this paper we used a newly proposed method: The Degenerate Unmixing and Estimation Technique (DUET). The method applies when sources are W-disjoint orthogonal; that is, when the time-frequency representations, of any two signals in the mixtures are disjoint sets. The method uses an online algorithm to perform gradient search for the mixing parameters, and simultaneously construct binary time-frequency masks that are used to partition one of the mixtures to recover the original source signals. Previous studies have demonstrated the robustness of the method. However, the investigation in this paper reveals significant drawbacks associated with the technique which should be addressed in the future.}},
  author       = {{Mohammed, Abbas and Ballal, Tariq and Grbic, Nedelko}},
  issn         = {{1210-2512}},
  language     = {{eng}},
  number       = {{4}},
  pages        = {{96--100}},
  publisher    = {{Czech Technical University}},
  series       = {{Radioengineering}},
  title        = {{Blind Source Separation Using Time-Frequency Masking}},
  url          = {{http://hdl.handle.net/11012/57331}},
  volume       = {{16}},
  year         = {{2007}},
}