The applications of neural networks in the core location analysis of extensive air showers

The authors describe the teaching and implementation of a neural network to estimate the core position and energy of extensive air showers recorded by the South Pole air shower experiment, SPASE. The neural network was found to be approximately 300 times faster than the traditional x2 minimization technique previously used and as accurate.