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One-Dimensional Kohonen's Lvq Nets for Multidimensional Patterns Recognition
International Journal of Applied Mathematics and Computer Science, Tome 10 (2000) no. 4, pp. 767-778
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A new neural network based pattern recognition algorithm is proposed. The method consists in preprocessing the multidimensional data, using a space-filling curve based transformation into the unit interval, and employing Kohonen's vector quantization algorithms (of SOM and LVQ types) in one dimension. The space-filling based transformation preserves the theoretical Bayes risk. Experiments show that such an approach can produce good or even better error rates than the classical LVQ performed in a multidimensional space.
Keywords: space-filling curve, pattern recognition, learning vector quantization, reduction of dimension
Mots-clés : krzywa przestrzenna, rozpoznawanie obrazów 
@article{IJAMCS_2000_10_4_a5,
     author = {Skubalska-Rafaj{\l}owicz, E.},
     title = {One-Dimensional {Kohonen's} {Lvq} {Nets} for {Multidimensional} {Patterns} {Recognition}},
     journal = {International Journal of Applied Mathematics and Computer Science},
     pages = {767--778},
     year = {2000},
     volume = {10},
     number = {4},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/IJAMCS_2000_10_4_a5/}
}
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Skubalska-Rafajłowicz, E. One-Dimensional Kohonen's Lvq Nets for Multidimensional Patterns Recognition. International Journal of Applied Mathematics and Computer Science, Tome 10 (2000) no. 4, pp. 767-778. http://geodesic.mathdoc.fr/item/IJAMCS_2000_10_4_a5/