Application of artificial neural networks in particle physics

The application of artificial neural networks in particle physics is reviewed. The use of feed-forward nets is most common for event classification and function approximation. This network type is best suited for a hardware implementation and special VLSI chips are available which are used in fast trigger processors. Also discussed are fully connected networks of the Hopfield type for pattern recognition in tracking detectors.