Adaptive resonance theory based artificial neural networks for treatment of open-category problems in chemical pattern recognition — application to UV-Vis and IR spectroscopy
- 1 May 1994
- journal article
- research article
- Published by Elsevier in Chemometrics and Intelligent Laboratory Systems
- Vol. 23 (2) , 309-329
- https://doi.org/10.1016/0169-7439(93)e0063-a
Abstract
No abstract availableThis publication has 39 references indexed in Scilit:
- Multicriteria target vector optimization of analytical procedures using a genetic algorithmAnalytica Chimica Acta, 1993
- Prediction of carbon-13 nuclear magnetic resonance chemical shifts by artificial neural networksAnalytical Chemistry, 1992
- Detection of odorants using an array of piezoelectric crystals and neural-network pattern recognitionAnalytica Chimica Acta, 1991
- Classification of Alloys with an Artificial Neural Network and Multivariate Calibration of Glow-Discharge Emission SpectraApplied Spectroscopy, 1991
- Comparison of the training of neural networks for quantitative x-ray fluorescence spectrometry by a genetic algorithm and backward error propagationAnalytica Chimica Acta, 1991
- Processing of signals from an ion-elective electrode array by a neural networkAnalytica Chimica Acta, 1990
- Identification capability of odor sensor using quartz-resonator array and neural-network pattern recognitionSensors and Actuators B: Chemical, 1990
- Evolutions in chemometrics. Plenary lectureThe Analyst, 1990
- Classification of mass spectra using adaptive digital learning networksAnalytical Chemistry, 1975
- Computerized learning machines applied to chemical problems. Molecular formula determination from low resolution mass spectrometryAnalytical Chemistry, 1969