On the Sensitivity Investigation of the Neural Network Implementing the Principal Component Analysis Method

Автоматика и вычислительная техника 2009
Artūrs Pčelkins, Arkādijs Borisovs

The efficiency of the proposed modification of the neural network implementing the principal component analysis (PCA) method is studied. A known neural network – the Hebbian filter- is chosen for the basic method. A test problem that allows varying the complexity of the input vectors is used to generate objects for testing both networks. Three series of experiments were conducted to compare the estimated efficiency of the Hebbian filter and the proposed architecture. The results of the experiments show the proposed modification to have an advantage for all the problems involved.

Keywords
neural networks, Hebbian filter, dimensionality reduction, principal component analysis, neural network sensitivity

Pčelkins, A., Borisovs, A. On the Sensitivity Investigation of the Neural Network Implementing the Principal Component Analysis Method. Автоматика и вычислительная техника, 2009, N 4, pp.37-47. ISSN 0132-4160.

Publication language
Russian (ru)