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Atoms of all channels, unite! Average case analysis of multi-channel sparse recovery using greedy algorithms

Pierre Vandergheynst, Rémi Gribonval, Karin Schnass

This paper provides new results on computing simultaneous sparse approximations of multichannel signals over redundant dictionaries using two greedy algorithms. The first one, p-thresholding, selects the S atoms that have the largest

p

-correlation while ...

2008

Analyse en composantes indépendantes

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A low complexity orthogonal matching pursuit for sparse signal approximation with shift-invariant dictionaries

An online Hebbian learning rule that performs Independent Component Analysis

Tracking Articulated Bodies using Generalized Expectation Maximization

Spike detection algorithm improvement, spike waveforms projections with PCA and hierarchical classification

Sparsity-based Source Separation with Scale-Discretized Steerable Wavelets

SENSITIVITY OF RISK INDICATORS UNDER MOTORWAY TRAFFIC REGIMES CLUSTERED BY SELF-ORGANIZING MAP

Atoms of all channels, unite! Average case analysis of multi-channel sparse recovery using greedy algorithms

A Neural Network based Regression Approach for Recognizing Simultaneous Speech

Efficient Data Flow Variable Length Decoding Implementation for the MPEG Reconfigurable Video Coding Framework

Video Decoder Reconfigurations and AVS Extensions in the New MPEG Reconfigurable Video Coding Framework

A low complexity orthogonal matching pursuit for sparse signal approximation with shift-invariant dictionaries

An online Hebbian learning rule that performs Independent Component Analysis

Spike detection algorithm improvement, spike waveforms projections with PCA and hierarchical classification

Tracking Articulated Bodies using Generalized Expectation Maximization

Atoms of all channels, unite! Average case analysis of multi-channel sparse recovery using greedy algorithms

Sparsity-based Source Separation with Scale-Discretized Steerable Wavelets

Efficient Data Flow Variable Length Decoding Implementation for the MPEG Reconfigurable Video Coding Framework

SENSITIVITY OF RISK INDICATORS UNDER MOTORWAY TRAFFIC REGIMES CLUSTERED BY SELF-ORGANIZING MAP

A Neural Network based Regression Approach for Recognizing Simultaneous Speech

Video Decoder Reconfigurations and AVS Extensions in the New MPEG Reconfigurable Video Coding Framework