Radiation exposure effects on the performance of an electrically trainable artificial neural network (ETANN)

The authors present the effects of radiation exposure on an analog neural network device. The neural network implements a fully parallel architecture integrating 10,240 analog non-volatile synapses fabricated in a CMOS process. Graceful degradation of forward propagation performance analog non-volatile synapses fabricated in a CMOS process. Graceful degradation of forward propagation performance was observed in units that were exposed to absorbed doses of up to 26 Krads (Si) of 10 MeV electrons. The units were exposed without bias, except for that due to the floating gates. Single chip solutions to two pattern recognition problems representing two levels of difficulty are employed for testing. Post-irradiation-effects are observed over the following weeks after exposure due to latent charge trapping mechanism in the oxides of the non-volatile floating gate structures. They show that with the suitable algorithm and model, units with apparently permanent damage can be retrained to 100% recognition performance