Theoretical analysis of the batch variant of the self-organizing feature map algorithm for 1-d networks mapping a continuous 1-d input space

 
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1998 (EN)
Theoretical analysis of the batch variant of the self-organizing feature map algorithm for 1-d networks mapping a continuous 1-d input space (EN)

Βασιλάς, Νικόλαος (EL)

Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Πληροφορικής Τ.Ε. (EL)

This work investigates the batch variant of Kohonen's self-organizing feature map (SOFM) algorithm both analytically and with simulations. In this algorithm, the winning neurons as well as the weight updates are computed in batch mode (epoch mode). It is shown that for 1-D maps and 1-D continuous input and weight spaces the strictly increasing or decreasing weight configurations form absorbing classes provided certain conditions on the parameters are satisfied. Ordering of the maps, convergence in distribution and asymptotic convergence are also proved analytically. Finally, simulations and comparisons with the original Kohonen algorithm on 1-D and 2-D maps are provided and are found to be in complete agreement with the theoretical results. (EN)

journalArticle

αυτο-οργανωμένοι χάρτες (EN)
Self-organizing maps (EN)
Markov processes (EN)
διαδικασίες Μάρκοβ (EN)
Algorithm (EN)
αλγόριθμος (EN)

ΤΕΙ Αθήνας (EL)
Technological Educational Institute of Athens (EN)

International Journal of Computer Mathematics (EN)

English

1998

DOI: 10.1080/00207169808804653

Taylor & Francis (EN)



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