Principal Components Analysis Competitive Learning
Principal Components Analysis Competitive Learning is a scholarly work by Ezequiel López-Rubio, José Antonio Gómez-Ruiz, José Muñoz-Pérez, and Juan Miguel Ortiz-de-Lazcano-Lobato, published in 2004 in ''Neural Computation''. The main subjects of the publication include data set, Competitive learning, pattern recognition, set, dimensionality reduction, principal, nonlinear dimensionality reduction, artificial intelligence, computer science, curse of dimensionality, Diffusion map, machine learning, artificial neural network, facial recognition system, independent component analysis, and principal component analysis. The experimental results authors present show the dimensionality-reduction capabilities of the model with multisensor images. .