Publication Details
Title: Kohonen Feature Maps and Growing Cell Structures–a Performance Comparison
Author: B. Fritzke
Group: ICSI Technical Reports
Date: May 1993
PDF: ftp://ftp.icsi.berkeley.edu/pub/techreports/1993/tr-93-025.pdf
Overview:
A performance comparison of two self-organizing networks, the Kohonen Feature Map and the recently proposed Growing Cell Structures is made. For this purpose several performance criteria for self-organizing networks are proposed and motivated. The models are tested with three example problems of increasing difficulty. The Kohonen Feature Map demonstrates slightly superior results only for the simplest problem. For the other more difficult and also more realistic problems the Growing Cell Structures exhibit significantly better performance by every criterion. Additional advantages of the new model are that all parameters are constant over time and that size as well as structure of the network are determined automatically. Keywords: feature map, incremental learning, Kohonen * Presented at NIPS 5 in Denver
Bibliographic Information:
ICSI Technical Report TR-93-025
Bibliographic Reference:
B. Fritzke. Kohonen Feature Maps and Growing Cell Structures–a Performance Comparison. ICSI Technical Report TR-93-025, May 1993
Author: B. Fritzke
Group: ICSI Technical Reports
Date: May 1993
PDF: ftp://ftp.icsi.berkeley.edu/pub/techreports/1993/tr-93-025.pdf
Overview:
A performance comparison of two self-organizing networks, the Kohonen Feature Map and the recently proposed Growing Cell Structures is made. For this purpose several performance criteria for self-organizing networks are proposed and motivated. The models are tested with three example problems of increasing difficulty. The Kohonen Feature Map demonstrates slightly superior results only for the simplest problem. For the other more difficult and also more realistic problems the Growing Cell Structures exhibit significantly better performance by every criterion. Additional advantages of the new model are that all parameters are constant over time and that size as well as structure of the network are determined automatically. Keywords: feature map, incremental learning, Kohonen * Presented at NIPS 5 in Denver
Bibliographic Information:
ICSI Technical Report TR-93-025
Bibliographic Reference:
B. Fritzke. Kohonen Feature Maps and Growing Cell Structures–a Performance Comparison. ICSI Technical Report TR-93-025, May 1993