A sublinear algorithm for the recovery of signals with sparse Fourier transform when many samples are missing

We present a sublinear randomized algorithm to compute a sparse Fourier transform for nonequispaced data of a special type. More precisely, we address the situation where a signal S is known to consist of N equispaced time samples, of which only L