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Learning through ferroelectric domain dynamics in solid-state synapses
oleh: Sören Boyn, Julie Grollier, Gwendal Lecerf, Bin Xu, Nicolas Locatelli, Stéphane Fusil, Stéphanie Girod, Cécile Carrétéro, Karin Garcia, Stéphane Xavier, Jean Tomas, Laurent Bellaiche, Manuel Bibes, Agnès Barthélémy, Sylvain Saïghi, Vincent Garcia
Format: | Article |
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Diterbitkan: | Nature Portfolio 2017-04-01 |
Deskripsi
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, Boynet al. establish a model that enables learning and retrieving patterns in a neural system.