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.