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Study of the Kohonen network with a discrete state space

✍ Scribed by Patrick Thiran; Martin Hasler


Publisher
Elsevier Science
Year
1995
Tongue
English
Weight
462 KB
Volume
38
Category
Article
ISSN
0378-4754

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✦ Synopsis


Digital (or mixed mode) circuit implementations of neural networks bring one major modification to their ideal, defectless models: quantization of the weights dynamics. Would this modification completely perturb the behavior of the network, it will never be possible to implement it on a digital (or mixed mode) VLSI chip. Clearly, the analysis of quantization effects is crucial for practical applications. It has been mainly studied for Hopfield networks and multi-layer networks.

We study this issue in the Kohonen network, since it has received little attention so far. A Kohonen net is a self-organising map preserving the topology of the input space (Kohonen, 1989). The first part of the paper is devoted to the mathematical treatment of the self-organisation property of a one-dimensional array with discrete weights. This property has been already established for continuous-valued weights, we will see that we need additional hypothesis to ensure a correct result when the weights are discrete-valued. The second part presents a qualitative extension of this analysis to more general cases.


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