A Principal Components Analysis Self-Organizing Neural Network Model and Computational Experiment

Ji Fu Nong

doi:10.4028/www.scientific.net/AMR.756-759.3330

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 756-759A Principal Components Analysis Self-Organizing...

A Principal Components Analysis Self-Organizing Neural Network Model and Computational Experiment

Abstract:

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.

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Periodical:

Advanced Materials Research (Volumes 756-759)

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3330-3335

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.756-759.3330

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Online since:

September 2013

Authors:

Ji Fu Nong

Keywords:

Competitive Learning, Pattern Recognition, Principal Component Analysis (PCA), Self-Organization

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