Abstract
We present in this paper the embedding of the Othogonal Weight Estimator (OWE) principle in Kohonen self-organizing maps (SOM). The resulting architecture is a context-independant classification system. The modification of the SOM architecture is that the weights of the SOM are computed by a MLP feds by the context of the presented pattern. We show the results on not trivial problem that underline the capacities of this new architecture.
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© 1997 Springer-Verlag Berlin Heidelberg
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Pican, N. (1997). Contextual kohonen SOM with orthogonal weight estimator principle. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020231
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DOI: https://doi.org/10.1007/BFb0020231
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-63631-1
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