A comparison of convex and non-convex compressed sensing applied to multidimensional NMR

► Compressed sensing (CS) is applied for the reconstruction of simulated and experimental NMR spectra. ► Two CS algorithms are used, employing convex and non-convex penalty function. ► The accuracy and robustness of the two approaches is compared. ► Additionally, comparison with multidimensional decomposition and direct FT is discussed. ► The non-convex CS outperforms conventional convex approach.