Inproceedings,
Novel similarity measure for comparing spectra (Poster)
ACS Meeting 2006, 85, page 1--8. (2006)
Abstract
Most available vector comparison methods such as the correlation coefficient 1 and Tanimoto coefficient 2 are only able to find pointwise similarities. Similarity criteria for spectra comparison should include information about the neighborhood of the corresponding items in order to identify shifted signals as well. So far, only few such methods have been described. A recent method by de Gelder et al. 3 is based on a locally weighted cross-correlation function being normalized with the geometric mean of the individual autocorrelation functions. A much better performance has been achieved with our novel similarity criterion called bin method.Similarity of related 1H NMR spectra has been successfully detected by a novel method based on dividing the spectra in bins. It has been shown that the correlation coefficient does not provide a useful similarity measure and that the recently introduced crosscorrelation-based method performs less well than our novel similarity measure.Application of the new method with spectra of two or more dimensions including image analysis is straightforward.
