Title :
Gamma-filter self-organising neural networks for unsupervised sequence processing
Author :
P.A. Estevez;R. Hernandez;C.A. Perez;C.M. Held
Author_Institution :
Department of Electrical Engineering and Advanced Mining Technology Center, Universidad de Chile
fDate :
4/14/2011 12:00:00 AM
Abstract :
Adding γ-filters to self-organising neural networks for unsupervised sequence processing is proposed. The proposed γ-context model is applied to self-organising maps and neural gas networks. The γ-context model is a generalisation that includes as a particular example the previously published merge-context model. The results show that the γ-context model outperforms the merge-context model in terms of temporal quantisation error and state-space representation.
Journal_Title :
Electronics Letters
DOI :
10.1049/el.2011.0115