Hierarchical growing cell structures

Vanco Burzevski, Chilukuri K Mohan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Scopus citations

Abstract

We propose a hierarchical self-organizing neural network with adaptive architecture and simple topological organization. This network combines features of Fritzke's Growing Cell Structures and traditional hierarchical clustering algorithms. The height and width of the tree structure depend on the user-specified level of error desired, and the weights in upper layers of the network do not change in later phases of the learning algorithm.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Neural Networks - Conference Proceedings
PublisherIEEE Computer Society
Pages1658-1663
Number of pages6
Volume3
StatePublished - 1996
EventProceedings of the 1996 IEEE International Conference on Neural Networks, ICNN. Part 1 (of 4) - Washington, DC, USA
Duration: Jun 3 1996Jun 6 1996

Other

OtherProceedings of the 1996 IEEE International Conference on Neural Networks, ICNN. Part 1 (of 4)
CityWashington, DC, USA
Period6/3/966/6/96

ASJC Scopus subject areas

  • Software

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  • Cite this

    Burzevski, V., & Mohan, C. K. (1996). Hierarchical growing cell structures. In IEEE International Conference on Neural Networks - Conference Proceedings (Vol. 3, pp. 1658-1663). IEEE Computer Society.