Self-Organisation in the SOM with a finite number of possible inputs

Abstract. Given a one dimensional SOM with a monotonically decreasing neighbourhood and an input distribution which is not Lebesque continuous, a set of su cient conditions and a Theorem are stated which ensure probability one organisation of the neuron weights. This leads to a rule for choosing the number of neurons and width of the neighbourhood to improve the chances of reaching an organised state in a practical implementation of the SOM.

• Type: Conference
• Year: 2000
• Where: ESANN
• Authors: John A. Flanagan
• Keywords: Dimensional Som, ESANN 2000, ESANN 2007, Neuron Weights, Su Cient Conditions