Principal component neural networks: theory and applications
Principal component neural networks: theory and applications
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Introduction to Machine Learning (Adaptive Computation and Machine Learning)
Introduction to Machine Learning (Adaptive Computation and Machine Learning)
| Hi-index | 0.00 |
The performance of a method for the reduction of the input space dimensionality of a physical or engineering problem is analyzed. The results of its application to several engineering problems are compared with those obtained by other well-known methods for the reduction of input space dimensionality, such as Principal Component Analysis and Independent Component Analysis. In order to carry out this study, the features extracted by the three methods were used as inputs to a feedforward neural network. The advantages of the proposed method are that it presents a computational complexity depending on the number of variables and guarantees dimensional homogeneity in the new space.