DocumentCode :
2507459
Title :
Analysis of neighborhood interaction in Kohonen neural networks
Author :
Lo, Zhen-Ping ; Fujita, Masahiro ; Bavarian, Behnam
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., Irvine, CA, USA
fYear :
1991
fDate :
30 Apr-2 May 1991
Firstpage :
246
Lastpage :
249
Abstract :
A formal analysis of the neighborhood interaction of Kohonen neural networks is presented. The authors propose a new neighborhood interaction to improve the topological order of the neural network. The neighborhood interaction which depends on lateral distance is motivated by anatomical evidence as opposed to what is currently used, which is a constant. The authors also mathematically show that using the new neighborhood interaction will enforce the topological order in the neighborhood set for every iteration. One simulation is presented to show that the topological order is improved by using the new neighborhood interaction
Keywords :
learning systems; neural nets; topology; Kohonen neural networks; anatomical evidence; lateral distance; learning rule; neighborhood interaction; self-organising feature map networks; spatial domain; topological order; topology preserving mapping; Algorithm design and analysis; Intelligent networks; Network topology; Neural networks; Neurons; Organizing; Self-organizing networks; Shape; Signal generators; Signal mapping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel Processing Symposium, 1991. Proceedings., Fifth International
Conference_Location :
Anaheim, CA
Print_ISBN :
0-8186-9167-0
Type :
conf
DOI :
10.1109/IPPS.1991.153786
Filename :
153786
Link To Document :
بازگشت