Enrico Gaggio
Study and Design of a Leaky Integrate-and-Fire Neuron based on Domain Wall motion.
Rel. Mariagrazia Graziano, Fabrizio Riente. Politecnico di Torino, Master of science program in Nanotechnologies For Icts, 2023
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Abstract
One of the most promising approaches for the next generation technologies is neuromorphic computing, which takes inspiration from the brain working principles to design systems with faster computing speed and higher energy efficiency than conventional technology. This is why, in the past years, the possibility of creating artificial neurons and artificial synapses has attracted great interest, leading to a great increase in the research regarding this kind of devices. Among the proposals that can be found in the literature there are spintronic neurons which are particularly interesting since they can take advantages of both electrical and magnetic properties of electrons, allowing for a potential increase of energy efficiency.
This thesis will concern the study and the design of a Leaky Integrate-and-Fire (LIF) neuron based on domain wall motion along a racetrack
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