Neural networks infrared spectrum interpretation

M.E. Munk, M.S. Madison and E.W. Robb, Neural network models for infrared spectrum interpretation. Microchim. Acta, 2 (1991) 505-524. 

Robb EW, Munk ME (1990) A neural network approach to infrared spectrum interpretation. Mikrochim Acta [Wien] 1990/1 131... 

Munk, M.E., Madison, M.S., and Robb, E.W., Neural Network Models for Infrared Spectrum Interpretation, Mikrochim. Acta, [Wien] 2, 505, 1991. 

Neural networks have been applied to infrared spectrum interpreting systems in many variations and applications. Anand introduced a neural network approach to analyze the presence of amino acids in protein molecules with a reliability of nearly 90% [37]. Robb used a linear neural network model for interpreting infrared spectra in routine analysis purposes with a similar performance [38]. Ehrentreich et al. used a counterpropagation (CPG) network based on a strategy of Novic and Zupan to model the correlation of structures and infrared spectra [39]. Penchev and colleagues compared three types of spectral features derived from infrared peak tables for their ability to be used in automatic classification of infrared spectra [40]. 

Algorithms Infrared Data Correlations with Chemical Structure Infrared Spectra Interpretation by the Characteristic Frequency Approach Machine Learning Techniques in Chemistry Molecular Models Visualization Neural Networks in Chemistry NMR Data Correlation with Chemical Structure Partial Least Squares Projections to Latent Structures (PLS) in Chemistry Shape Analysis Spectroscopic Databases Spectroscopy Computational Methods Structure Determination by Computer-based Spectrum Interpretation Zeolites Applications of Computational Methods. 

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