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Proceedings Paper

Classification of infrared spectra of organophosphorus compounds with artificial neural networks
Author(s): Howard T. Mayfield; DeLyle Eastwood; Larry W. Burggraf
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Paper Abstract

We examine the use of artificial neural networks to classify IR spectra of organophosphorus pesticides and chemically related compounds. The spectra used were contributed from commercial libraries, government agencies, and government contractors and include spectra of pesticides, industrial precursors, hydrolysis products and other organophosphorus compounds. The data were pretreated to reduce artifacts arising from the variety of collection sources. The treated spectra were divided into spectral 'bins' of equal frequency width and transduced into data vectors whose elements consisted of the average absorbance value of the corresponding spectral bin. The spectral data vectors served as inputs to neural networks examined as spectral classifiers.

Paper Details

Date Published: 16 December 1999
PDF: 9 pages
Proc. SPIE 3854, Pattern Recognition, Chemometrics, and Imaging for Optical Environmental Monitoring, (16 December 1999); doi: 10.1117/12.372886
Show Author Affiliations
Howard T. Mayfield, Air Force Research Lab. (United States)
DeLyle Eastwood, Air Force Institute of Technology (United States)
Larry W. Burggraf, Air Force Institute of Technology (United States)


Published in SPIE Proceedings Vol. 3854:
Pattern Recognition, Chemometrics, and Imaging for Optical Environmental Monitoring
Khalid J. Siddiqui; DeLyle Eastwood, Editor(s)

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