Learning through ferroelectric domain dynamics in solid-state synapses

Accurate modelling of memristor dynamics is essential for the development of autonomous learning in artificial neural networks. Through a combined theoretical and experimental study of the polarization switching process in ferroelectric memristors, Boyn et al. establish a model that enables learning and retrieving patterns in a neural system.