Abstract--In this paper we address the task of accurately reconstructing a distributed signal through the collection of a small number of samples at a data gathering point using Co...
Riccardo Masiero, Giorgio Quer, Michele Rossi, Mic...
Abstract--This paper develops an optimal decentralized algorithm for sparse signal recovery and demonstrates its application in monitoring localized phenomena using energy-constrai...
This paper develops theoretical results regarding noisy 1-bit compressed sensing and sparse binomial regression. We demonstrate that a single convex program gives an accurate estim...
This paper introduces a new algorithm for reconstructing signals with sparse spectrums from noisy compressive measurements. The proposed model-based algorithm takes the signal str...
This short note studies a variation of the Compressed Sensing paradigm introduced recently by Vaswani et al., i.e. the recovery of sparse signals from a certain number of linear m...