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RBF-sítě s dynamickou architekturou / RBF-networks with a dynamic architecture

In this master thesis I recapitulated several methods for clustering input data. Two well known clustering algorithms, concretely K-means algorithm and Fuzzy C-means (FCM) algorithm, were described in the submitted work. I presented several methods, which could help estimate the optimal number of clusters. Further, I described Kohonen maps and two models of Kohonen's maps with dynamically changing structure, namely Kohonen map with growing grid and the model of growing neural gas. At last I described quite new model of radial basis function neural networks. I presented several learning algorithms for this model of neural networks. In the end of this work I made some clustering experiments with real data. This data describes the international trade among states of the whole world.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:297903
Date January 2011
CreatorsJakubík, Miroslav
ContributorsMrázová, Iveta, Kukačka, Marek
Source SetsCzech ETDs
LanguageSlovak
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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