The morphological score and its application to chemical rank determination

Abstract Most spectra with structural information are smooth. Making use of this feature, a new procedure is proposed for automatic chemical rank determination. In order to avoid accumulation of noise, key spectra instead of the full matrix are analyzed in the procedure. A simplified morphological factor, morphological score (MS), is proposed. The noise level of morphological analysis is established with the help of F -test. The proposed procedure was successfully applied in the study of self-association behavior of alcohol. Results show that two classes of aggregates contribute to near infrared (NIR) spectra besides the monomer. Data sets produced by other techniques were also tested.

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