Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 27,
  • Issue 5,
  • pp. 371-376
  • (1973)

Interpretation of Infrared Spectra Using Pattern Recognition Techniques

Not Accessible

Your library or personal account may give you access

Abstract

The pattern recognition technique utilizing adaptive binary pattern classifiers has been applied to the interpretation of infrared spectra. The binary pattern classifiers have been trained to determine the chemical classes of x-y digitized infrared spectra. High predictive abilities have been obtained in classifying unknown spectra. A new training procedure for binary pattern classifiers has been developed, and it has been used to classify ir spectra into chemical classes. Pattern classifiers trained in the conventional way and by the new procedure have been used in conjunction with feature selection, and it is shown that a small fraction of the data is necessary to classify these infrared spectra successfully into chemical classes.

PDF Article
More Like This
Disease pattern recognition in infrared spectra of human sera with diabetes mellitus as an example

Wolfgang Petrich, Brion Dolenko, Johanna Früh, Manfred Ganz, Helmut Greger, Stephan Jacob, Franz Keller, Alexander E. Nikulin, Matthias Otto, Ortrud Quarder, Ray L. Somorjai, Arnulf Staib, Gerhard Werner, and Hans Wielinger
Appl. Opt. 39(19) 3372-3379 (2000)

Automated interpretation of LIBS spectra using a fuzzy logic inference engine

Jeremy J. Hatch, Timothy R. McJunkin, Cynthia Hanson, and Jill R. Scott
Appl. Opt. 51(7) B155-B164 (2012)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.