Blind signal separation

Known as: Self-modeling mixture analysis, Multivariate curve resolution, BSS 
Blind signal separation, also known as blind source separation, is the separation of a set of source signals from a set of mixed signals, without the… (More)
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Papers overview

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Review
2017
Review
2017
Speech enhancement and separation are core problems in audio signal processing, with commercial applications in devices as… (More)
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Highly Cited
2004
Highly Cited
2004
Binary time-frequency masks are powerful tools for the separation of sources from a single mixture. Perfect demixing via binary… (More)
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Highly Cited
2000
Highly Cited
2000
This paper describes a new blind signal separation method using the directivity pattems of the microphone array. In this method… (More)
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Highly Cited
2000
Highly Cited
2000
| Acoustic signals recorded simultaneously in a reverberant environment can be described as sums of di erently convolved sources… (More)
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Highly Cited
1999
Highly Cited
1999
Recently many new Blind Signal Separation BSS algorithms have been introduced Authors evaluate the performance of their… (More)
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Review
1998
Review
1998
Blind signal separation (BSS) and independent component analysis (ICA) are emerging techniques of array processing and data… (More)
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Highly Cited
1997
Highly Cited
1997
Algorithms for the blind separation of sources can be derived from several different principles. This article shows that the… (More)
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Highly Cited
1997
Highly Cited
1997
Separation of sources consists of recovering a set of signals of which only instantaneous linear mixtures are observed. In many… (More)
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Highly Cited
1995
Highly Cited
1995
A new on-line learning algorithm which minimizes a statistical dependency among outputs is derived for blind separation of mixed… (More)
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Highly Cited
1995
Highly Cited
1995
We derive a new self-organizing learning algorithm that maximizes the information transferred in a network of nonlinear units… (More)
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