Foate, JoshuaValdez, LuisAlamaniotis, Miltos2022-08-032022-08-032022-07-28https://hdl.handle.net/20.500.12588/1075Collected data using a radiation detector to identify anomalies in the presence of naturally occurring radioactive material. Samples of the anomaly signals were put into a Hopfield neural network to train the network to identify whether data from the detector was an anomaly or background radiation. Converting our data into a 3SAT (3- Satisfiability) problem and use Grover's algorithm to find the solutions for Hopfield Artificial Neural Network memoryen-USundergraduate student worksPoster