activity
20052023
most citedCompressed sensing imaging techniques for radio interferometry

268 citations · 581 across the 35 of their papers we have counts for

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Showing 2020Show all

10 papers · 1 filter

cs.IT2020

Keep the phase! Signal recovery in phase-only compressive sensing

Laurent Jacques, Thomas Feuillen

We demonstrate that a sparse signal can be estimated from the phase of complex random measurements, in a "phase-only compressive sensing" (PO-CS) scenario. With high probability an…

eess.SP2020

Going Below and Beyond, Off-the-Grid Velocity Estimation from 1-bit Radar Measurements

Gilles Monnoyer de Galland, Thomas Feuillen, Luc Vandendorpe +1

In this paper we propose to bridge the gap between using extremely low resolution 1-bit measurements and estimating targets' parameters, such as their velocities, that exist in a c…

cs.LG2020

When compressive learning fails: blame the decoder or the sketch?

Vincent Schellekens, Laurent Jacques

In compressive learning, a mixture model (a set of centroids or a Gaussian mixture) is learned from a sketch vector, that serves as a highly compressed representation of the datase…

eess.SP2020

One Bit to Rule Them All : Binarizing the Reconstruction in 1-bit Compressive Sensing

Thomas Feuillen, Mike Davies, Luc Vandendorpe +1

This work focuses on the reconstruction of sparse signals from their 1-bit measurements. The context is the one of 1-bit compressive sensing where the measurements amount to quanti…

astro-ph.IM2020

MAYONNAISE: a morphological components analysis pipeline for circumstellar disks and exoplanets imaging in the near infrared

Benoît Pairet, Faustine Cantalloube, Laurent Jacques

Imaging circumstellar disks in the near-infrared provides unprecedented information about the formation and evolution of planetary systems. However, current post-processing techniq…

eess.SP2020

Factorization over interpolation: A fast continuous orthogonal matching pursuit

Gilles Monnoyer de Galland, Luc Vandendorpe, Laurent Jacques

We propose a fast greedy algorithm to compute sparse representations of signals from continuous dictionaries that are factorizable, i.e., with atoms that can be separated as a prod…