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Corrections to "On the Stable Recovery of the Sparsest Overcomplete Representations in Presence of Noise" [Oct 10 5396-5400]

IEEE transactions on signal processing, 2011-04, Vol.59 (4), p.1913-1913

2011

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A Fast Approach for Overcomplete Sparse Decomposition Based on Smoothed \ell ^ Norm

IEEE transactions on signal processing, 2009-01, Vol.57 (1), p.289-301

2009

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Corrections to

IEEE transactions on signal processing, 2011-04, Vol.59 (4), p.1913-1913

2011

Volltextzugriff (PDF)

Approximated CrameraRao bound for estimating the mixing matrix in the two-sensor noisy Sparse Component Analysis (SCA)

Digital signal processing, 2013-05, Vol.23 (3), p.771-779

2013

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A Geometric Approach for Separating Several Speech Signals

Independent Component Analysis and Blind Signal Separation, 2004, p.798-806

2004

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Filtering noisy ECG signals using the extended kalman filter based on a modified dynamic ECG model

Computers in Cardiology, 2005, 2005, p.1017-1020

2005

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Blind separation of bilinear mixtures using mutual information minimization

2009 IEEE International Workshop on Machine Learning for Signal Processing, 2009, p.1-6

2009

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Blind Source Separation by Adaptive Estimation of Score Function Difference

Independent Component Analysis and Blind Signal Separation, 2004, p.9-17

2004

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A Fast Approach for Overcomplete Sparse Decomposition Based on Smoothed ell 0 Norm

IEEE transactions on signal processing, 2009-01, Vol.57 (1)

2009

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A Fast Approach for Overcomplete Sparse Decomposition Based on Smoothed [Formula Omitted] Norm

IEEE transactions on signal processing, 2009-01, Vol.57 (1), p.289

2009

Volltextzugriff (PDF)

A Fast Approach for Overcomplete Sparse Decomposition Based on Smoothedell {0} Norm

IEEE transactions on signal processing, 2009-01, Vol.57 (1), p.289-301

2009

Volltextzugriff (PDF)

A new approach in decomposition over multiple-overcomplete dictionaries with application to image inpainting

2009 IEEE International Workshop on Machine Learning for Signal Processing, 2009, p.1-6

2009

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Compressed sensing Block MAP-LMS adaptive filter for sparse channel estimation and a Bayesian Cramer-Rao bound

2009 IEEE International Workshop on Machine Learning for Signal Processing, 2009, p.1-6

2009

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Thresholded smoothed-ℓ0(SL0) dictionary learning for sparse representations

2009 IEEE International Conference on Acoustics, Speech and Signal Processing, 2009, p.1825-1828

2009

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ECG denoising and compression by sparse 2D separable transform with overcomplete mixed dictionaries

2009 IEEE International Workshop on Machine Learning for Signal Processing, 2009, p.1-6

2009

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A minimization-projection (MP) approach for blind separating convolutive mixtures

2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004, Vol.5, p.V-533

2004

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Watermarking Based on Independent Component Analysis in Spatial Domain

2011 UkSim 13th International Conference on Computer Modelling and Simulation, 2011, p.299-303

2011

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The 2016 Signal Separation Evaluation Campaign

Latent Variable Analysis and Signal Separation, 2017, p.323-332

2017

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k/K-Nearest Neighborhood Criterion for Improving Locally Linear Embedding

2009 Sixth International Conference on Computer Graphics, Imaging and Visualization, 2009, p.392-397

2009

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Two Dimensional Compressive Classifier for Sparse Images

2009 Sixth International Conference on Computer Graphics, Imaging and Visualization, 2009, p.402-405

2009

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Monoaural Audio Source Separation Using Deep Convolutional Neural Networks

Latent Variable Analysis and Signal Separation, p.258-266

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Toward Rank Disaggregation: An Approach Based on Linear Programming and Latent Variable Analysis

Latent Variable Analysis and Signal Separation, p.192-200

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Estimating the mixing matrix in Sparse Component Analysis (SCA) using EM algorithm and iterative Bayesian clustering

2008 16th European Signal Processing Conference, 2008, p.1-5

2008

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Blind Source Separation of Single Channel Mixture Using Tensorization and Tensor Diagonalization

Latent Variable Analysis and Signal Separation, p.36-46

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A Blind Identification and Source Separation Method Based on Subspace Intersections for Hyperspectral Astrophysical Data

Latent Variable Analysis and Signal Separation, p.367-380

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Corrections to "On the Stable Recovery of the Sparsest Overcomplete Representations in Presence of Noise" [Oct 10 5396-5400]

A Fast Approach for Overcomplete Sparse Decomposition Based on Smoothed \ell ^ Norm

Corrections to

Approximated CrameraRao bound for estimating the mixing matrix in the two-sensor noisy Sparse Component Analysis (SCA)

A Geometric Approach for Separating Several Speech Signals

Filtering noisy ECG signals using the extended kalman filter based on a modified dynamic ECG model

Blind separation of bilinear mixtures using mutual information minimization

Blind Source Separation by Adaptive Estimation of Score Function Difference

A Fast Approach for Overcomplete Sparse Decomposition Based on Smoothed ell 0 Norm

A Fast Approach for Overcomplete Sparse Decomposition Based on Smoothed [Formula Omitted] Norm

A Fast Approach for Overcomplete Sparse Decomposition Based on Smoothedell {0} Norm

A new approach in decomposition over multiple-overcomplete dictionaries with application to image inpainting

Compressed sensing Block MAP-LMS adaptive filter for sparse channel estimation and a Bayesian Cramer-Rao bound

Thresholded smoothed-ℓ0(SL0) dictionary learning for sparse representations

ECG denoising and compression by sparse 2D separable transform with overcomplete mixed dictionaries

A minimization-projection (MP) approach for blind separating convolutive mixtures

Watermarking Based on Independent Component Analysis in Spatial Domain

The 2016 Signal Separation Evaluation Campaign

k/K-Nearest Neighborhood Criterion for Improving Locally Linear Embedding

Two Dimensional Compressive Classifier for Sparse Images

Monoaural Audio Source Separation Using Deep Convolutional Neural Networks

Toward Rank Disaggregation: An Approach Based on Linear Programming and Latent Variable Analysis

Estimating the mixing matrix in Sparse Component Analysis (SCA) using EM algorithm and iterative Bayesian clustering

Blind Source Separation of Single Channel Mixture Using Tensorization and Tensor Diagonalization

A Blind Identification and Source Separation Method Based on Subspace Intersections for Hyperspectral Astrophysical Data

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