Neural Network System for the Identification of Infrared Spectra
- 1 May 1992
- journal article
- research article
- Published by SAGE Publications in Applied Spectroscopy
- Vol. 46 (5) , 807-810
- https://doi.org/10.1366/0003702924124619
Abstract
A neural network system has been developed on a personal computer to identify 1129 infrared spectra. The system is composed of two steps of networks. The first step classifies 1129 spectra into 40 categories, and each unit of the output layer is connected to one of the 40 networks in the second step, which identify each spectrum. Each network is composed of three layers. The input, intermediate, and output layers are composed of 250, 40, and 40 units, respectively. Intensity data at 250 wavenumber points between 1800 and 550 cm−1 of the infrared spectra are entered into the input layer of each network. The training of the networks was carried out with the spectral data of 1129 compounds stored in the SDBS system, and thus the networks were successfully constructed. On the basis of the results, the system has been developed by preparing pre- and post-processing programs. The system can identify each unknown spectrum within 0.1 s, and is quite efficient for identifying infrared spectra on a personal computer.Keywords
This publication has 8 references indexed in Scilit:
- Classification of Mass Spectral Data Using Neural NetworksPublished by Springer Nature ,1991
- MSnet: A Neural Network which Classifies Mass SpectraTetrahedron Computer Methodology, 1990
- Spectroscopic calibration and quantitation using artificial neural networksAnalytical Chemistry, 1990
- Application of Fuzzy Neural Network to Spectrum IdentificationPublished by Springer Nature ,1990
- Neural NetworksPublished by Springer Nature ,1990
- Optical neural net for classifying imaging spectrometer dataApplied Optics, 1989
- An Integrated Spectral Data Base System Including IR, MS, 1H-NMR, 13C-NMR, ESR and Raman SpectraAnalytical Sciences, 1988
- Learning representations by back-propagating errorsNature, 1986