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Hamburg 12/8/1993
NeXT Application
Adaptive Resonance Theorie (ART)
Neural network models based on the ART developped by
Carpenter and Grossberg have the ability of stable unsupervised
learning.
In this package you will find a NeTXStep application (tested for
release 3.0)
ART.app and its source code (*.m, *.h, *.nib)
simulating the basic ART-2 network for recognition and
classification of analog patterns. Additionally you find a modifi-
cation of the network, which allows distributed classification
by of superposition of orthogonal pattern components.
A PostScript file ART.ps contains a detailed description in German
language of my ART-2 modification, its results and a rough
introduction to the usage of ART.app.
This document is the outcome of my project work at the institute
of Technical Computer Science VI at TU Hamburg-Harburg, Germany.
For fundamental understanding of Grossberg's Adaptive Resonance
Theory and derived neural networks please have a look at
(1) Carpenter, G.A., Grossberg, S.: A massively parallel
architecture for a self-organizing neural pattern recognition
machine, Computer Vision, Graphics and Image Processing,
Academic Press, Inc., 1987
(2) Carpenter, G.A., Grossberg, S.: ART-2: self-organization of
stable category recognition codes for analog input patterns,
Applied Optics, Vol.26, 1987
For questions and suggestions please contact
e-Mail: ti6cmt@tick.ti6.tu-harburg.de
Christian Mueller-Tomfelde
These are the contents of the former NiCE NeXT User Group NeXTSTEP/OpenStep software archive, currently hosted by Netfuture.ch.