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)
Wikipedia

Related topics

Related topics

6 relations
ChirpNoise reductionSampling (signal processing)White noise
(More)

Broader (1)

Signal processing

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2012
Highly Cited
2012
Subspace Methods for Joint Sparse Recovery
We propose robust and efficient algorithms for the joint sparse recovery problem in compressed sensing, which simultaneously… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 5
  • figure 4
Is this relevant?
Highly Cited
2008
Highly Cited
2008
Hyperspectral Subspace Identification
Signal subspace identification is a crucial first step in many hyperspectral processing algorithms such as target detection… (More)
  • figure 1
  • figure 2
  • table I
  • figure 3
  • figure 4
Is this relevant?
Highly Cited
2008
Highly Cited
2008
Higher-Order SVD-Based Subspace Estimation to Improve the Parameter Estimation Accuracy in Multidimensional Harmonic Retrieval Problems
Multidimensional harmonic retrieval problems are encountered in a variety of signal processing applications including radar… (More)
  • table I
  • table II
  • figure 1
  • figure 2
  • figure 3
Is this relevant?
Highly Cited
2003
Highly Cited
2003
Robust adaptive beamforming for general-rank signal models
The performance of adaptive beamforming methods is known to degrade severely in the presence of even small mismatches between the… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 5
  • figure 4
Is this relevant?
Highly Cited
2003
Highly Cited
2003
Incorporating the human hearing properties in the signal subspace approach for speech enhancement
The major drawback of most noise reduction methods in speech applications is the annoying residual noise known as musical noise… (More)
  • figure 1
  • figure 2
  • figure 3
  • table II
  • figure 4
Is this relevant?
Highly Cited
2003
Highly Cited
2003
A generalized subspace approach for enhancing speech corrupted by colored noise
A generalized subspace approach is proposed for enhancement of speech corrupted by colored noise. A nonunitary transform, based… (More)
  • figure 1
  • table I
  • table II
  • table III
  • table IV
Is this relevant?
Highly Cited
2002
Highly Cited
2002
Blind noise reduction for multisensory signals using ICA and subspace filtering, with application to EEG analysis
 In many applications of signal processing, especially in communications and biomedicine, preprocessing is necessary to remove… (More)
  • figure 1
  • figure 2
  • figure 3
  • table 1
  • figure 4
Is this relevant?
Highly Cited
1997
Highly Cited
1997
A signal subspace tracking algorithm for microphone array processing of speech
This paper presents a method of adaptive microphone array beamforming using matched filters with signal subspace tracking. Our… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
Highly Cited
1992
Highly Cited
1992
Analysis of subspace fitting and ML techniques for parameter estimation from sensor array data
Signal parameter estimation from sensor array data is a problem that is encountered in many engineering applications. Under the… (More)
Is this relevant?
Highly Cited
1988
Highly Cited
1988
Focussing matrices for coherent signal-subspace processing
In this paper, a new class of focussing matrices is proposed for use in the Coherent Signal-Subspace Method (CSM) [ 11. When the… (More)
  • figure I
  • figure 3
  • table I
  • figure 6
  • figure 8
Is this relevant?