Publications associées à Matching pursuit

Jump-Sparse and Sparse Recovery Using Potts Functionals

We recover jump-sparse and sparse signals from blurred incomplete data corrupted by (possibly non-Gaussian) noise using inverse Potts energy functionals. We obtain analytical results (existence of minimizers, complexity) on inverse Potts functionals and pr ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Structured Sparsity Models for Reverberant Speech Separation

Hervé Bourlard, Volkan Cevher, Afsaneh Asaei, Mohammad Golbabaee

We tackle the multi-party speech recovery problem through modeling the acoustic of the reverberant chambers. Our approach exploits structured sparsity models to perform room modeling and speech recovery. We propose a scheme for characterizing the room acou ...

2014

Learning Parametric Dictionaries for Signals on Graphs

Pascal Frossard, David Shuman

In sparse signal representation, the choice of a dictionary often involves a tradeoff between two desirable properties – the ability to adapt to specific signal data and a fast implementation of the dictionary. To sparsely represent signals residing on wei ...

Institute of Electrical and Electronics Engineers2014

Convex Optimization Approaches for Blind Sensor Calibration using Sparsity

Rémi Gribonval, Gilles Puy

We investigate a compressive sensing framework in which the sensors introduce a distortion to the measurements in the form of unknown gains. We focus on blind calibration, using measures performed on multiple unknown (but sparse) signals and formulate the ...

Institute of Electrical and Electronics Engineers2014

Sparse Gammatone Signal Model Predicts Perceived Noise Intrusiveness

Hervé Bourlard, Raphaël Marc Ullmann

Is it possible to predict the intrusiveness of background noise in speech signals as perceived by humans? Such a question is important to the automatic evaluation of speech enhancement systems, including those designed for new wideband speech telephony, an ...

Idiap2014

A Convex Solution to Disparity Estimation from Light Fields via the Primal-Dual Method

Pierre Vandergheynst, Mahdad Hosseini Kamal

We present a novel approach to the reconstruction of depth from light field data. Our method uses dictionary representations and group sparsity constraints to derive a convex formulation. Although our solution results in an increase of the problem dimensio ...

2014

LAYOUT ASSESSMENT METHOD AND SYSTEM

Frank Grégoire Jean de Morsier, Virginia Estellers Casas, Nathalie Casati, Maria Gabrani

Candidate layout patterns can be assessed using a sparse pattern dictionary of known design layout patterns by determining sparse coefficients for each candidate pattern, reconstructing the respective candidate pattern, and determining reconstruction error ...

U.S. Patent and Trademark Office; U.S. DEPARTMENT OF COMMERCE2013

Sparsity averaging for radio-interferometric imaging

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Jason Douglas McEwen

We propose a novel regularization method for compressive imaging in the context of the CS theory with coherent and redundant dictionaries. The approach relies on the conjecture that natural images exhibit strong average sparsity over multiple coherent fram ...

2013

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Matching pursuit

Jump-Sparse and Sparse Recovery Using Potts Functionals

Structured Sparsity Models for Reverberant Speech Separation

Learning Parametric Dictionaries for Signals on Graphs

Convex Optimization Approaches for Blind Sensor Calibration using Sparsity

A survey of uncertainty principles and some signal processing applications

Sparse Gammatone Signal Model Predicts Perceived Noise Intrusiveness

A Convex Solution to Disparity Estimation from Light Fields via the Primal-Dual Method

LAYOUT ASSESSMENT METHOD AND SYSTEM

Image registration with sparse approximations in parametric dictionaries

Sparsity averaging for radio-interferometric imaging

Graph Chatbot

Chattez avec Graph Search

Convex Optimization Approaches for Blind Sensor Calibration using Sparsity

Jump-Sparse and Sparse Recovery Using Potts Functionals

A survey of uncertainty principles and some signal processing applications

Learning Parametric Dictionaries for Signals on Graphs

Sparse Gammatone Signal Model Predicts Perceived Noise Intrusiveness

A Convex Solution to Disparity Estimation from Light Fields via the Primal-Dual Method

LAYOUT ASSESSMENT METHOD AND SYSTEM

Image registration with sparse approximations in parametric dictionaries

Sparsity averaging for radio-interferometric imaging