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Blind Denoising with Random Greedy Pursuits
Manuel Moussallam, Alexandre Gramfort, Laurent Daudet +1
Denoising methods require some assumptions about the signal of interest and the noise. While most denoising procedures require some knowledge about the noise level, which may be un…
Imaging With Nature: Compressive Imaging Using a Multiply Scattering Medium
Antoine Liutkus, David Martina, Sébastien Popoff +6
The recent theory of compressive sensing leverages upon the structure of signals to acquire them with much fewer measurements than was previously thought necessary, and certainly w…
Convex Optimization Approaches for Blind Sensor Calibration using Sparsity
Cagdas Bilen, Gilles Puy, Rémi Gribonval +1
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 me…
Source localization in reverberant rooms using sparse modeling and narrowband measurements
Gilles Chardon, Laurent Daudet
We study two cases of acoustic source localization in a reverberant room, from a number of point-wise narrowband measurements. In the first case, the room is perfectly known. We sh…
Low-complexity computation of plate eigenmodes with Vekua approximations and the Method of Particular Solutions
Gilles Chardon, Laurent Daudet
This paper extends the Method of Particular Solutions (MPS) to the computation of eigenfrequencies and eigenmodes of plates. Specific approximation schemes are developed, with plan…
Sampling and reconstruction of solutions to the Helmholtz equation
Gilles Chardon, Albert Cohen, Laurent Daudet
We consider the inverse problem of reconstructing general solutions to the Helmholtz equation on some domain from their values at scattered points . Thi…