DocumentCode
3850268
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
Volume
47
Issue
8
fYear
2011
fDate
4/14/2011 12:00:00 AM
Firstpage
494
Lastpage
496
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
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el.2011.0115
Filename
5751790
Link To Document