Abstract
The principles of learning strategy of Kohonen and counterpropagation neural networks are introduced. The advantages of unsupervised learning are discussed. The self-organizing maps produced in both methods are suitable for a wide range of applications. Here, we present an example of Kohonen and counterpropagation neural networks used for mapping, interpretation, and simulation of infrared (IR) spectra. The artificial neural network models were trained for prediction of structural fragments of an unknown compound from its infrared spectrum. The training set contained over 3,200 IR spectra of diverse compounds of known chemical structure. The structure-spectra relationship was encompassed by the counterpropagation neural network, which assigned structural fragments to individual compounds within certain probability limits, assessed from the predictions of test compounds. The counterpropagation neural network model for prediction of fragments of chemical structure is reversible, which means that, for a given structural domain, limited to the training data set in the study, it can be used to simulate the IR spectrum of a chemical defined with a set of structural fragments.
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References
Kohonen T (1988) Self-organization and associative memory. Springer-Verlag, Berlin.
Kohonen T (2001) Self organizing maps (3rd edn). Springer, Heidelberg.
Dayhof J (1990) Neural network architectures, an introduction. Van Nostrand Reinhold, New York.
Carpenter G, Grossberg S (1988) The art of adaptive pattern recognition by a self-organizing neural network. IEEE Computer 21:77–88.
Hecht-Nielsen R (1987) Counterpropagation networks. Appl. Optics 26:4979–4984.
Zupan J, Gasteiger J (1999) Neural networks in chemistry and drug design (2nd edn). Wiley-VCH, Weinheim.
Zupan J, Novič M, Ruisanchez I (1997) Kohonen and counterpropagation artificial neural networks in analytical chemistry: tutorial. Chemometr Intell Lab Syst 38:1–23.
Razinger M, Novič M (1990) Reduction of the information space for data collections. In: Zupan J (ed) PCs for chemist. Elsevier, Amsterdam, pp. 89–103.
Graff DK (1995) Fourier and Hadamard: transforms in spectroscopy, J Chem Ed 72:304–309.
Novič M, Zupan J (1995). Investigation of infrared spectra-structure correlation using Kohonen and counterpropagation neural-network, J Chem Info Comp Sci 35:454–466.
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© 2008 Humana Press, a part of Springer Science + Business Media, LLC
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Novic, M. (2008). Kohonen and Counterpropagation Neural Networks Applied for Mapping and Interpretation of IR Spectra. In: Livingstone, D.J. (eds) Artificial Neural Networks. Methods in Molecular Biology™, vol 458. Humana Press. https://doi.org/10.1007/978-1-60327-101-1_4
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DOI: https://doi.org/10.1007/978-1-60327-101-1_4
Publisher Name: Humana Press
Print ISBN: 978-1-58829-718-1
Online ISBN: 978-1-60327-101-1
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