A parameter-free non-growing self-organizing map based upon gravitational principles: Algorithm and applications-Reference-Cited by-同舟云学术

A parameter-free non-growing self-organizing map based upon gravitational principles: Algorithm and applications

Published:1996 Issue: Volume: Page:827-832
ISSN:0302-9743
Container-title:Artificial Neural Networks — ICANN 96
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Author:

Lange J. S.,Freiesleben H.

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/3-540-61510-5_139.pdf

Reference9 articles.

1. Kohonen, T.: Self-Organization and Associative Memory. Springer Series in Information Sciences 8, 1984, pp. 125

2. Fritzke, B.: Growing Cell Structures — a self-organizing network for unsupervised and supervised learning. Neural Networks 7 (1994) 1441–1460

3. Martinetz, T., Schulten, K.: A „neural-gas” network learns topologies. Artificial Neural Networks, Editors: Kohonen, T., Mäkisara, K., Simula, O., Kangas, J., North-Holland, Amsterdam, 1991, pp. 397

4. Behrmann, K.-O.: Leistungsuntersuchung des “Dynamischen Link-Matchings” und Vergleich mit dem Kohonen-Algorithmus. Diploma Thesis, Institut für Neuroinformatik, Ruhr-Universität Bochum, 1993

5. Lange, J. S.: Extraktion von Bremsstrahlungsereignissen in Proton-Proton-Reaktionen durch Anwendung künstlicher neuronaler Netze. Ph.D. Thesis, Institut für Experimentalphysik I, Ruhr-Universität Bochum, 1994

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