论文信息 - Raman spectrometry and neural networks for the classification of wood types. 2. Kohonen self-organizing maps

Raman spectrometry and neural networks for the classification of wood types. 2. Kohonen self-organizing maps

Abstract One- and two-dimensional Kohonen self-organizing maps (SOMs) were successfully used for the unsupervised differentiation of the Fourier transform Raman spectra of hardwoods from softwoods. The SOMs were also applied to differentiate temperate woods from tropical woods, and results showed that the two types of woods could only be partly differentiated. A semi-quantitative method that is based on the Euclidean distances of the weight matrix has been developed to assist the automatic clustering of the neurons in a two-dimensional SOM.

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