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A neural network approach to infrared spectrum interpretation

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Abstract

The simple linear neural network model was investigated as a method for automated interpretation of infrared spectra. The model was trained using a database of infrared spectra of organic compounds of known structure. The model was able to learn, without any prior input of spectrum-structure correlations, to recognize and identify 76 functional groupings with accuracies ranging from fair to excellent. The effect of network input parameters and of training set composition were studied, and several sources of spurious correlations were identified and corrected.

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Authors and Affiliations

  1. Department of Chemistry and Chemical Engineering, Stevens Institute of Technology, 07030, Hoboken, NJ, USA

    Ernest W. Robb

  2. Department of Chemistry, Arizona State University, 85287-1604, Tempe, AZ, USA

    Morton E. Munk

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  1. Ernest W. Robb
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  2. Morton E. Munk
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Dedicated to Professor W. Simon on the occasion of his 60th birthday

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Robb, E.W., Munk, M.E. A neural network approach to infrared spectrum interpretation. Mikrochim Acta 100, 131–155 (1990). https://doi.org/10.1007/BF01244838

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  • DOI: https://doi.org/10.1007/BF01244838

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