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Training and synchronizing oscillator networks with Equilibrium Propagation
Théophile Rageau, Julie Grollier
Oscillator networks represent a promising technology for unconventional computing and artificial intelligence. Thus far, these systems have primarily been demonstrated in small-sca…
Easy-plane spin Hall nano-oscillators as spiking neurons for neuromorphic computing
Danijela Marković, Matthew W. Daniels, Pankaj Sethi +3
We show analytically using a macrospin approximation that easy-plane spin Hall nano-oscillators excited by a spin-current polarized perpendicularly to the easy-plane have phase dyn…
Hardware realization of the multiply and accumulate operation on radio-frequency signals with magnetic tunnel junctions
Nathan Leroux, Alice Mizrahi, Danijela Markovic +7
Artificial neural networks are a valuable tool for radio-frequency (RF) signal classification in many applications, but digitization of analog signals and the use of general purpos…
Radio-Frequency Multiply-And-Accumulate Operations with Spintronic Synapses
N. Leroux, D. Marković, E. Martin +4
Exploiting the physics of nanoelectronic devices is a major lead for implementing compact, fast, and energy efficient artificial intelligence. In this work, we propose an original…
Chaos and relaxation oscillations in spin-torque windmill neurons
Rie Matsumoto, Steven Lequeux, Hiroshi Imamura +1
Spintronic neurons which emit sharp voltage spikes are required for the realization of hardware neural networks enabling fast data processing with low-power consumption. In many ne…