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Bibliographic Metadata
- TitleTopoART: A Topology Learning Hierarchical ART Network
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- LanguageEnglish
- Document typeConference Proceedings
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- ISBN978-3-642-15824-7
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- IIIF
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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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