  The extremely high rate of events that will be produced in the future Large
Hadron Collider requires the triggering mechanism to take precise decisions in
a few nano-seconds. We present a study which used an artificial neural network
triggering algorithm and compared it to the performance of a dedicated
electronic muon triggering system. Relatively simple architecture was used to
solve a complicated inverse problem. A comparison with a realistic example of
the ATLAS first level trigger simulation was in favour of the neural network. A
similar architecture trained after the simulation of the electronics first
trigger stage showed a further background rejection.
