Efficient unsupervised training algorithm for self-organizing networks

Authors

Felicisimo Domingo ⋅ PH National Institute of Physics, University of the Philippines Diliman
Caesar Saloma ⋅ PH National Institute of Physics, University of the Philippines Diliman

Abstract

We develop a very efficient training algorithm for self-organizing networks (SON) which have run times that are linear with both the number of desired output vectors and training set vectors, respectively. The algorithm is very efficient compared with older ones which have run-times that are quadratic (~N2) with the number of desired output vectors. Run-times for both cases were predicted from models derived from the algorithms and were also confirmed by actual programs.

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Issue

1996: Proceedings of the 14th National Physics Congress of the Samahang Pisika ng Pilipinas

Article ID

SPP-1996-IC-05

Section

Instrumentation and Computational Physics

Published

1996-12-06

How to Cite

[1]

F Domingo and C Saloma, Efficient unsupervised training algorithm for self-organizing networks, Proceedings of the Samahang Pisika ng Pilipinas 14, SPP-1996-IC-05 (1996). URL: https://proceedings.spp-online.org/article/view/SPP-1996-IC-05.