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1 February 1994 Modeling Kohonen networks by attributed parallel array systems
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Proceedings Volume 2093, Substance Identification Analytics; (1994) https://doi.org/10.1117/12.172497
Event: Substance Identification Technologies, 1993, Innsbruck, Austria
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.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rudolf Freund and Friedrich Tafill "Modeling Kohonen networks by attributed parallel array systems", Proc. SPIE 2093, Substance Identification Analytics, (1 February 1994); https://doi.org/10.1117/12.172497
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