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The detection of air-shower events via radio signals requires to develop atrigger algorithm for a clean discrimination between signal and backgroundevents in order to reduce the data stream coming from false triggers. In thiscontribution we will describe an approach to trigger air-shower events on asingle-antenna level as well as performing an online reconstruction of theshower parameters using neural networks.

Towards online triggering for the radio detection of air showers using deep neural networks