Dynamic Self-Organising Map

Nicolas P. Rougier 1 Yann Boniface 1
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : We present in this paper a variation of the self-organising map algorithm where the original time-dependent (learning rate and neighbourhood) learning function is replaced by a time-invariant one. This allows for on-line and continuous learning on both static and dynamic data distributions. One of the property of the newly proposed algorithm is that it does not fit the magnification law and the achieved vector density is not directly proportional to the density of the distribution as found in most vector quantisation algorithms. From a biological point of view, this algorithm sheds light on cortical plasticity seen as a dynamic and tight coupling between the environment and the model.
Type de document :
Article dans une revue
Neurocomputing, Elsevier, 2011, 74 (11), pp.1840-1847. 〈10.1016/j.neucom.2010.06.034〉
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Soumis le : mardi 29 juin 2010 - 09:20:32
Dernière modification le : jeudi 11 janvier 2018 - 06:19:48
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Nicolas P. Rougier, Yann Boniface. Dynamic Self-Organising Map. Neurocomputing, Elsevier, 2011, 74 (11), pp.1840-1847. 〈10.1016/j.neucom.2010.06.034〉. 〈inria-00495827〉



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