Concept

Signal separation

Publications associées (64)

Conditions for recovery of sparse signals correlated by local transforms

This paper addresses the problem of correct recovery of multiple sparse correlated signals using distributed thresholding. We consider the scenario where multiple sensors capture the same event, but observe different signals that are correlated by local tr ...

2009

Procédé et un dispositif d'estimation de signaux de source issus d'un signal de mélange

Rémi Gribonval

The invention pertains to the field of methods for estimating source signals from a multichannel mixture signal, and the aim of the invention is to carry out a reliable estimation of the properties of source signals without necessarily requiring prior info ...

2009

Adaptive tracking of EEG components

Jean-Marc Vesin, Laurent Renaud Uldry, Cédric Duchene, Yann Prudat

In this chapter, we propose a novel method for tracking oscillatory components in EEG signals by means of an adaptive filter-bank. The specificity of our tracking algorithm is to maximize the oscillatory behavior of its output rather than its spectral powe ...

Springer2009

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

Pierre Vandergheynst, Rémi Gribonval

We propose a variant of Orthogonal Matching Pursuit (OMP), called LoCOMP, for scalable sparse signal approximation. The algorithm is designed for shift- invariant signal dictionaries with localized atoms, such as time-frequency dictionaries, and achieves a ...

2009

Sparsity-based Source Separation with Scale-Discretized Steerable Wavelets

Pierre Vandergheynst, Yves Wiaux

In this talk, we discuss the issue of source separation in a signal on the sphere or on the plane, relying on the sparsity of one signal component in a scale-discretized steerable wavelet basis. The steerability of wavelets allows to probe in detail the lo ...

2008

Hardware-efficient steering matrix computation architecture for MIMO communication systems

Carl Christian Sten Dominic Senning, Christoph Studer

Beamforming (BF) improves the error rate performance of multiple-input multiple-output (MIMO) wireless communication systems by spatial separation of the transmitted data streams. Spatial separation is achieved by multiplication of the transmit vector by a ...

2008

A Neural Network based Regression Approach for Recognizing Simultaneous Speech

Hervé Bourlard, John David Scott Dines, Weifeng Li

This paper presents our approach for automatic speech recognition (ASR) of overlapping speech. Our system consists of two principal components: a speech separation component and a feature estmation component. In the speech separation phase, we first estima ...

IDIAP2008

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

Minimum Mutual Information Beamforming for Simultaneous Active Speakers

In this work, we consider an acoustic beamforming application where two speakers are simultaneously active. We construct one subband-domain beamformer in \emph{generalized sidelobe canceller} (GSC) configuration for each source. In contrast to normal pract ...

IDIAP2007

Adaptive Beamforming with a Minimum Mutual Information Criterion

IDIAP2007

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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

p

-correlation while ...

2008