One of the major challenges is using subspace-based approaches for the determination of the parameters of one- or multidimensional signals is their practical applicability on real data containing \emph{damped} exponentials. In this paper, we present a comparison survey of low complexity subspace-based methods and we focus on 2-D nuclear magnetic resonance (NMR) spectroscopy application. We first present free search 2-D estimation approaches for damped sinusoids and we analyze their performances using simulated signals. Then, we present the results obtained on real 2-D NMR data.
