Abstract
A method of comparing two spectra using linear and quadratic regression is described. For every wavelength, the log(1/R) value of the first spectrum is used as x, that of the second as y. The correlation coefficient (r) is used to compute a similarity index which can be used to test for identity. The method has the advantage of comparing whole spectra, rather than only certain peaks, while reducing the data to a single variable. For crystalline solids with different particle sizes, better results are obtained if a quadratic rather than a linear equation is used. This procedure allows the successful identification of isomers and sugars, even when there is considerable variation in particle size.
Get full access to this article
View all access options for this article.
