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Genetic optimization of self-organizing feature maps

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2 Author(s)
Harp, S.A. ; Honeywell SSDC, Minneapolis, MN, USA ; Samad, T.

The authors present an application of the genetic algorithm to the design of Kohonen self-organizing feature maps. The genetic algorithm is used to optimize various parameters of the network model for a given problem. Performance criteria relevant to clustering or vector quantization applications are considered: root mean square error and an information-theoretic map entropy measure. Experimental results demonstrate the effectiveness of the approach, and suggest some interesting generalizations

Published in:

Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on  (Volume:i )

Date of Conference:

8-14 Jul 1991