TopoART: A Topology Learning Hierarchical ART Network

  • Marko Tscherepanow
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6354)


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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  1. 1.
    Vigdor, B., Lerner, B.: Accurate and fast off and online fuzzy ARTMAP-based image classification with application to genetic abnormality diagnosis. IEEE Transactions on Neural Networks 17(5), 1288–1300 (2006)CrossRefGoogle Scholar
  2. 2.
    Goerick, C., Schmüdderich, J., Bolder, B., Janßen, H., Gienger, M., Bendig, A., Heckmann, M., Rodemann, T., Brandl, H., Domont, X., Mikhailova, I.: Interactive online multimodal association for internal concept building in humanoids. In: Proceedings of the IEEE-RAS International Conference on Humanoid Robots, pp. 411–418 (2009)Google Scholar
  3. 3.
    Tscherepanow, M., Jensen, N., Kummert, F.: An incremental approach to automated protein localisation. BMC Bioinformatics 9(445) (2008)Google Scholar
  4. 4.
    MacQueen, J.: Some methods for classification and analysis of multivariate observations. In: Proceedings of the Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281–297 (1967)Google Scholar
  5. 5.
    Linde, Y., Buzo, A., Gray, R.M.: An algorithm for vector quantizer design. IEEE Transactions on Communications COM-28, 84–95 (1980)CrossRefGoogle Scholar
  6. 6.
    Kohonen, T.: Self-organized formation of topologically correct feature maps. Biological Cybernetics 43(1), 59–69 (1982)MATHCrossRefMathSciNetGoogle Scholar
  7. 7.
    Fritzke, B.: A growing neural gas network learns topologies. In: Neural Information Processing Systems, pp. 625–632 (1994)Google Scholar
  8. 8.
    Grossberg, S.: Competitive learning: From interactive activation to adaptive resonance. Cognitive Science 11, 23–63 (1987)CrossRefGoogle Scholar
  9. 9.
    Anagnostopoulos, G.C., Georgiopoulos, M.: Hypersphere ART and ARTMAP for unsupervised and supervised incremental learning. In: Proceedings of the International Joint Conference on Neural Networks, vol. 6, pp. 59–64 (2000)Google Scholar
  10. 10.
    Anagnostopoulos, G.C., Georgiopoulos, M.: Ellipsoid ART and ARTMAP for incremental clustering and classification. In: Proceedings of the International Joint Conference on Neural Networks, vol. 2, pp. 1221–1226 (2001)Google Scholar
  11. 11.
    Carpenter, G.A., Grossberg, S., Rosen, D.B.: Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system. Neural Networks 4, 759–771 (1991)CrossRefGoogle Scholar
  12. 12.
    Furao, S., Hasegawa, O.: An incremental network for on-line unsupervised classification and topology learning. Neural Networks 19, 90–106 (2006)MATHCrossRefGoogle Scholar
  13. 13.
    Furao, S., Ogura, T., Hasegawa, O.: An enhanced self-organizing incremental neural network for online unsupervised learning. Neural Networks 20, 893–903 (2007)MATHCrossRefGoogle Scholar
  14. 14.
    Tscherepanow, M., Hillebrand, M., Hegel, F., Wrede, B., Kummert, F.: Direct imitation of human facial expressions by a user-interface robot. In: Proceedings of the IEEE-RAS International Conference on Humanoid Robots, pp. 154–160 (2009)Google Scholar
  15. 15.
    Xu, R., Wunsch II, D.C.: Clustering. Wiley–IEEE Press (2009)Google Scholar
  16. 16.
    Tscherepanow, M.: Image analysis methods for location proteomics. PhD thesis, Faculty of Technology, Bielefeld University (2008)Google Scholar

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© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Marko Tscherepanow
    • 1
  1. 1.Applied InformaticsBielefeld UniversityBielefeldGermany

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