@misc{Najman_Krzysztof_Zastosowanie_2009,
 author={Najman, Krzysztof},
 year={2009},
 rights={Wszystkie prawa zastrzeżone (Copyright)},
 description={Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu = Research Papers of Wrocław University of Economics; 2009; Nr 47, s. 196-204},
 publisher={Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu},
 language={pol},
 abstract={One of the more effective methods in cluster analysis are unsupervised neural networks, for example Self Organizing Map, SOM. The problem which can appear in large data sets is a priori the network's structure. SOM could be time consuming and require powerful computers, it has tendency to twine and possess many neurons which do not take part in learning. It seems that unsupervised growing neural gas (GNG) with dynamic structure does not have these disadvantages. The main goal of research presented in this paper is hypothesis verification that the GNG network has large potential in cluster analysis. Theoretical principles, properties of this method, simulation research and opinions are presented. (original abstract)},
 type={artykuł},
 title={Zastosowanie nienadzorowanych sieci neuronowych typu Growing Neural Gas w analizie skupień},
}