no code implementations • 2 Dec 2020 • Sophie M. Fosson
Recovering the digital input of a time-discrete linear system from its (noisy) output is a significant challenge in the fields of data transmission, deconvolution, channel equalization, and inverse modeling.
Optimization and Control Systems and Control Systems and Control
1 code implementation • 31 Jan 2020 • Sophie M. Fosson
The development of online algorithms to track time-varying systems has drawn a lot of attention in the last years, in particular in the framework of online convex optimization.
no code implementations • 9 Sep 2019 • Vito Cerone, Sophie M. Fosson, Diego Regruto
We consider the problem of the recovery of a k-sparse vector from compressed linear measurements when data are corrupted by a quantization noise.
no code implementations • 30 May 2019 • Sophie M. Fosson, Mohammad Abuabiah
The recovery of signals with finite-valued components from few linear measurements is a problem with widespread applications and interesting mathematical characteristics.
1 code implementation • 7 Dec 2018 • Sophie M. Fosson
In this letter, we propose a new convergence analysis of a Lasso l1 reweighting method, based on the observation that the algorithm is an alternated convex search for a biconvex problem.
no code implementations • 7 Jul 2017 • Attilio Fiandrotti, Sophie M. Fosson, Chiara Ravazzi, Enrico Magli
Finally, we practically demonstrate our algorithms in a typical application of circulant matrices: deblurring a sparse astronomical image in the compressed domain.