Signal subspace

Known as: Subspace filtering 
In signal processing, signal subspace methods are empirical linear methods for dimensionality reduction and noise reduction. These approaches have… (More)
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Highly Cited
2012
Highly Cited
2012
We propose robust and efficient algorithms for the joint sparse recovery problem in compressed sensing, which simultaneously… (More)
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Highly Cited
2008
Highly Cited
2008
Signal subspace identification is a crucial first step in many hyperspectral processing algorithms such as target detection… (More)
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Highly Cited
2008
Highly Cited
2008
Multidimensional harmonic retrieval problems are encountered in a variety of signal processing applications including radar… (More)
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Highly Cited
2003
Highly Cited
2003
The performance of adaptive beamforming methods is known to degrade severely in the presence of even small mismatches between the… (More)
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Highly Cited
2003
Highly Cited
2003
The major drawback of most noise reduction methods in speech applications is the annoying residual noise known as musical noise… (More)
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Highly Cited
2003
Highly Cited
2003
A generalized subspace approach is proposed for enhancement of speech corrupted by colored noise. A nonunitary transform, based… (More)
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Highly Cited
2002
Highly Cited
2002
 In many applications of signal processing, especially in communications and biomedicine, preprocessing is necessary to remove… (More)
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Highly Cited
1997
Highly Cited
1997
This paper presents a method of adaptive microphone array beamforming using matched filters with signal subspace tracking. Our… (More)
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Highly Cited
1992
Highly Cited
1992
Signal parameter estimation from sensor array data is a problem that is encountered in many engineering applications. Under the… (More)
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Highly Cited
1988
Highly Cited
1988
In this paper, a new class of focussing matrices is proposed for use in the Coherent Signal-Subspace Method (CSM) [ 11. When the… (More)
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