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.
Recommended Citation
Burzevski, Vanco and Mohan, Chilukuri K., "Hierarchical Growing Cell Structures" (1996). L.C. Smith College of Engineering and Computer Science - Former Departments, Centers, Institutes and Projects. Paper 22.
http://surface.syr.edu/lcsmith_other/22
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.