The Principal Components Analysis Self-Organizing Map

Authors:
Ezequiel López-Rubio;José Muñoz-Pérez;José Antonio Gómez-Ruiz
Affiliations:
-;-;-
Venue:
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Year:
2002

Citing 2
Cited 0

Two-dimensional Gabor-type receptive field as derived by mutual information maximization

Neural Networks
Handwritten digit recognition by adaptive-subspace self-organizing map (ASSOM)

IEEE Transactions on Neural Networks

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Abstract

We propose a new self-organizing neural model that performs Principal Components Analysis (PCA). It is also related to the ASSOM network, but its training equations are simpler. Furthermore, it does not need any grouping of the input samples by episodes. Experimental results are reported, which show that the new model has better performance than the ASSOM network in a number of benchmark problems.