DocumentCode
1843678
Title
An empirical study of neighbourhood decay in Kohonen´s self organising map
Author
Keith-Magee, Russell ; Venkatesh, Svetha ; Takatsuka, Masahiro
Author_Institution
Sch. of Comput., Curtin Univ. of Technol., Perth, WA, Australia
Volume
3
fYear
1999
fDate
1999
Firstpage
1953
Abstract
In this paper, empirical results are presented which suggest that size and rate of decay of region size plays a much more significant role in the learning, and especially the development of topographic feature maps. Using these results as a basis, a scheme for decaying region size during SOM training is proposed. The proposed technique provides near optimal training time. This scheme avoids the need for sophisticated learning gain decay schemes, and precludes the need for a priori knowledge of likely training times. This scheme also has some potential uses for continuous learning
Keywords
curve fitting; learning (artificial intelligence); optimisation; self-organising feature maps; topology; Kohonen self organising map; SOM learning; continuous learning; decaying region size; gain decay; goodness of fit; neighbourhood decay; optimisation; topographic feature maps; Algorithm design and analysis; Biological processes; Biological system modeling; Biology computing; Brain modeling; Geography; Graphics; Iterative algorithms; Performance analysis; Performance gain;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-5529-6
Type
conf
DOI
10.1109/IJCNN.1999.832682
Filename
832682
Link To Document