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Proceedings Paper

Modeling Kohonen networks by attributed parallel array systems
Author(s): Rudolf Freund; Friedrich Tafill
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Paper Abstract

The concept of n-dimensional attributed parallel array systems is introduced and shown to be a useful tool for the formal description of the static as well as the dynamic characteristics of neural networks. Because of the underlying grid structure. Kohonen's model of self-organizing feature maps is especially well suited for being represented by n-dimensional attributed parallel array systems. Using our formal description model we prove that Kohonen's global algorithm for the adaption of the weights of the neurons in a fully connected network can be simulated in a network with locally bounded connections, which can be represented by an n- dimensional attributed parallel array system containing only parallel array productions with a bounded neighborhood. These results show that our model of n-dimensional attributed parallel array systems can be used as a specification language for various models of neural networks and as a formal tool for proving specific characteristic features of these networks.

Paper Details

Date Published: 1 February 1994
PDF: 12 pages
Proc. SPIE 2093, Substance Identification Analytics, (1 February 1994); doi: 10.1117/12.172497
Show Author Affiliations
Rudolf Freund, Technical Univ. of Vienna (Austria)
Friedrich Tafill, Technical Univ. of Vienna (Austria)

Published in SPIE Proceedings Vol. 2093:
Substance Identification Analytics
James L. Flanagan; Richard J. Mammone; Albert E. Brandenstein; Edward Roy Pike M.D.; Stelios C. A. Thomopoulos; Marie-Paule Boyer; H. K. Huang; Osman M. Ratib, Editor(s)

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