DocumentCode
2430614
Title
A new quantitative measure of topology preservation in Kohonen´s feature maps
Author
Villmann, Th. ; Der, R. ; Martinetz, Th
Author_Institution
Inst. of Inf., Leipzig Univ., Germany
Volume
2
fYear
1994
fDate
27 Jun-2 Jul 1994
Firstpage
645
Abstract
In this paper we give a new approach for quantifying topology preservation using explicitly the structure of the data manifold. It can be applied to linear and nonlinear data manifolds M. Further, this method allows one to quantify the range of folds. Our approach employs what we call the topographic function, which is defined based on the so called masked Voronoi polyhedra introduced by Martinetz (1993) for defining neighbourhood and topology preservation of feature maps
Keywords
learning (artificial intelligence); self-organising feature maps; topology; Kohonen´s feature maps; data manifold; masked Voronoi polyhedra; quantitative measure; topographic function; topology preservation; Euclidean distance; Graphics; Informatics; Lattices; Particle measurements; Research and development; Robots; Topology;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1901-X
Type
conf
DOI
10.1109/ICNN.1994.374251
Filename
374251
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