Spike detection from inaccurate samplings

This article investigates the support detection problem using the LASSO estimator in the space of measures. More precisely, we study the recovery of a discrete measure (spike train) from few noisy observations (Fourier samples, moments…) using an ${\mathrm{\ell }}_1$-regularization procedure. In particular, we provide an explicit quantitative localization of the spikes.