Alternatively, a more general statistical approach relying on peak matching is required. A few approaches can be found in the literature that match and compare HSQC spectra. Porzel et al. and Pretsch et al. both used a grid-based approach that divides the spectrum into a grid of a given resolution and assigns it with zeros and ones based on the absence/presence of a peak, resulting in a binary fingerprint for a given molecule. This algorithm provides a quick way for deduplicating spectra from databases. However, this approach's lack of peak-to-peak matching and sensitivity to grid resolution can result in decreased accuracy when compared to a one-to-one peak matching technique. Pierre et al. later developed a discrete selfadaptive differential evolution (dSADE) approach and improved the runtime speed of one-to-one peak matching methodology with an affinity matrix approach. Nonetheless, even this improved algorithm takes roughly 1 hour to match two spectra with 100 peaks (on a 1.8