  We study the electron/pion identification performance of the ALICE Transition
Radiation Detector (TRD) prototypes using a neural network (NN) algorithm.
Measurements were carried out for particle momenta from 2 to 6 GeV/c. An
improvement in pion rejection by about a factor of 3 is obtained with NN
compared to standard likelihood methods.
