A principal components analysis self-organizing neural network model and computational experiment
- 10.2991/iccia.2012.209How to use a DOI?
- Self-organization, Principal component analysis, Competitive learning, Pattern recognition
We propose a new self-organizing neural model that performs principal components analysis. It is also related to the adaptive subspace self-organizing map (ASSOM) network, but its training equations are simpler. Experimental results are reported, which show that the new model has better performance than the ASSOM network.
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Jifu Nong PY - 2014/05 DA - 2014/05 TI - A principal components analysis self-organizing neural network model and computational experiment BT - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012) PB - Atlantis Press SP - 859 EP - 862 SN - 1951-6851 UR - https://doi.org/10.2991/iccia.2012.209 DO - 10.2991/iccia.2012.209 ID - Nong2014/05 ER -