Document Type

Article

Date

1996

Embargo Period

8-2012

Keywords

hierarchical self-organizing neural network, HiGS, Fritzke's Growing Cell Structures

Language

English

Disciplines

Computer Sciences

Description/Abstract

We propose a hierarchical self-organizing neural network ("HiGS") 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. Parameters such as node deletion rate are adaptively modified by the learning algorithm.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

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