Self-organizing feature maps

T. Kohonen, Self Organization and Associated Memory. Springer-Verlag, Heidelberg, 1989. W.J. Meissen, J.R.M. Smits, L.M.C. Buydens and G. Kateman, Using artificial neural networks for solving chemical problems. II. Kohonen self-organizing feature maps and Hopfield networks. Chemom. Intell. Lab. Syst., 23 (1994) 267-291. 

All of the studies above have used back propagation multilayer perceptrons and many other varieties of neural network exist that have been applied to PyMS data. These include minimal neural networks,117119 radial basis functions,114120 self-organizing feature maps,110121 and autoassociative neural networks.122123... 

Also known as a Self-Organizing Feature Map or SOFM, or a Kohonen map after its inventor. 

A. Samecka-Cymerman, A. Stankiewicz, K. Kolon and A. J. Kempers, Self-organizing feature map (neural networks) as a tool in classification of the relations between chemical composition of aquatic bryophytes and types of streambeds in the Tatra national park in Poland, Chemosphere, 67(5), 2007, 954-960. 

A specialized method for similarity-based visualization of high-dimensional data is formed by self-organizing feature maps (SOM). The data items are arranged on a two-dimensional plane with the aid of neural networks, especially Kohonen nets. Similarity between data items is represented by spacial closeness, while large distances indicate major dissimilarities [968]. At the authors department, a system called MIDAS had already been developed which combines strategies for the creation of feature maps with the supervised generation of fuzzy-terms from the maps [967]. 

Sklorz, S. A Method for Data Analysis Based on Self Organizing Feature Maps. In Proceedings of the Internal. Symposium on Soft Computing for Industry (ISSCr96), Montpellier, Prance (May 1996)... 

Flame Identification with Self-Organizing Feature Maps.342... 

Kohonen networks are also termed self-organizing nets or self-organizing feature maps. 

Neural networks have also been developed to address the clustering aspect of unsupervised learning. These networks compute self-organizing feature maps in which examples with similar features appear in clusters." See Neural Networks in Chemistry. 

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