TopoART: A Topology Learning Hierarchical ART Network

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Titel
TopoART: A Topology Learning Hierarchical ART Network
Verfasser
Tscherepanow, Marko
Herausgeber
Diamantaras, Konstantinos ; Duch, Wlodek ; Iliadis, Lazaros S.
Erschienen
2010
Sprache
Englisch
Dokumenttyp
Konferenzband
Schlagwörter
hierarchical clustering / on-line learning / Adaptive Resonance Theory / topology learning
ISBN
978-3-642-15824-7
URN
urn:nbn:de:0070-pub-19255964
DOI
10.1007/978-3-642-15825-4_21

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Abstract

In this paper, a novel unsupervised neural network combining elements from Adaptive Resonance Theory and topology learning neural networks, in particular the Self-Organising Incremental Neural Network, is introduced. It enables stable on-line clustering of stationary and non-stationary input data. In addition, two representations reflecting different levels of detail are learnt simultaneously. Furthermore, the network is designed in such a way that its sensitivity to noise is diminished, which renders it suitable for the application to real-world problems.

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