268 citations · 1.4k across the 80 of their papers we have counts for
29 papers · 1 filter
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…
The importance of phase in complex compressive sensing
Laurent Jacques, Thomas Feuillen
We consider the question of estimating a real low-complexity signal (such as a sparse vector or a low-rank matrix) from the phase of complex random measurements. We show that in th…
Close Encounters of the Binary Kind: Signal Reconstruction Guarantees for Compressive Hadamard Sampling with Haar Wavelet Basis
Amirafshar Moshtaghpour, José M. Bioucas Dias, Laurent Jacques
We investigate the problems of 1-D and 2-D signal recovery from subsampled Hadamard measurements using Haar wavelet sparsity prior. These problems are of interest in, e.g., computa…
One-Bit Sensing of Low-Rank and Bisparse Matrices
Simon Foucart, Laurent Jacques
This note studies the worst-case recovery error of low-rank and bisparse matrices as a function of the number of one-bit measurements used to acquire them. First, by way of the con…
Proceedings of the fourth "international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques" (iTWIST'18)
Sandrine Anthoine, Yannick Boursier, Laurent Jacques
The iTWIST workshop series aim at fostering collaboration between international scientific teams for developing new theories, applications and generalizations of low-complexity mod…
Taking the edge off quantization: projected back projection in dithered compressive sensing
Chunlei Xu, Vincent Schellekens, Laurent Jacques
Quantized compressive sensing (QCS) deals with the problem of representing compressive signal measurements with finite precision representation, i.e., a mandatory process in any pr…