The PCA Method in Neural Networks

In the identification of e, μ and π particles at Beijing Spectrometer (BES) experiment with neural networks, the original input variables are reorganized by using PCA (Principal Component Analysis) method to form a set of irrelevant ones. The correlations between original input variables are thus eliminated, and the number of input variables is reduced. A higher speed and better operation capability are achieved.