Pattern recognition of particle tracks using principal component analysis and artificial neural network

A new method is suggested for pattern recognition of particle tracks based on a combined approach of both artificial neural network (ANN) and principal component analysis (PCA). It is seen that in high multiplicity environment, neither the PCA nor the ANN method is satisfactory when used separately as a track classifier. Best performance is achieved when the data are preprocessed using PCA technique, before it is fed to the backpropagated neural network.