Using neural networks as an event trigger in elementary particle physics experiments

Elementary particle physics experiments often have to deal with high data rates. In order to avoid having to write out all data that is occurring online processors, triggers are used to cull out the uninteresting data. These triggers are based on some particular aspect of the physics being examined. At times these aspects are often equivalent to simple pattern recognition problems. The reliability of artificial neural networks (ANNs) in pattern recognition problems in many fields has been well demonstrated. We present here the results of a study on the feasibility of using ANNs as an online trigger for high energy physics experiments