The authors demonstrate that the computational capabilities of Kohonen's algorithm provide an unified approach to such diverse fields as sensory mappings, combinatorial optimization, and learning in motor control. For a discrete probability distribution of the training inputs, the formation of the mapping can be described as a probabilistic descent in a potential. In view of their wide applicability, the principles of the algorithm might also be inherent to the maturation of biological brains and could help to achieve a better understanding of these processes from a more unified point of view.
|Original language||English (US)|
|Title of host publication||IEEE Int Conf on Neural Networks|
|Publisher||Publ by IEEE|
|Number of pages||8|
|State||Published - 1988|
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