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Growing a hypercubical output space in a self-organizing feature map.

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Bibliographic Details
Title: Growing a hypercubical output space in a self-organizing feature map.
Authors: Bauer, Hans-Ulrich, Villmann, Thomas
Source: IEEE Transactions on Neural Networks. Mar97, Vol. 8 Issue 2, p218. 9p. 6 Diagrams, 1 Chart, 9 Graphs.
Subjects: MAP (Computer program language), Algorithms
Abstract: Presents the growing self-organizing map (GSOM) which enhances a widespread map self-organization processes and Kohonen's self-organizing feature map (SOFM), by an adaptation of the output space grid during learning. Kohonen algorithm for self-organizing feature maps; GSOM-algorithm for maps with hypercubical output spaces; Examples of maps; Discussion of the study.
Database: Engineering Source
Description
Abstract:Presents the growing self-organizing map (GSOM) which enhances a widespread map self-organization processes and Kohonen's self-organizing feature map (SOFM), by an adaptation of the output space grid during learning. Kohonen algorithm for self-organizing feature maps; GSOM-algorithm for maps with hypercubical output spaces; Examples of maps; Discussion of the study.
ISSN:10459227
DOI:10.1109/72.557659