175 citations · 243 across the 4 of their papers we have counts for
11 papers
Convolutional Neural Networks with Radio-Frequency Spintronic Nano-Devices
Nathan Leroux, Arnaud De Riz, Dédalo Sanz-Hernández +3
Convolutional neural networks are state-of-the-art and ubiquitous in modern signal processing and machine vision. Nowadays, hardware solutions based on emerging nanodevices are des…
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…
Physics for Neuromorphic Computing
Danijela Markovic, Alice Mizrahi, Damien Querlioz +1
Neuromorphic computing takes inspiration from the brain to create energy efficient hardware for information processing, capable of highly sophisticated tasks. In this article, we m…
Wireless communication between two magnetic tunnel junctions acting as oscillator and diode
Danijela Marković, Nathan Leroux, Alice Mizrahi +7
Magnetic tunnel junctions are nanoscale spintronic devices with microwave generation and detection capabilities. Here we use the rectification effect called "spin-diode" in a magne…
Energy-efficient stochastic computing with superparamagnetic tunnel junctions
Matthew W. Daniels, Advait Madhavan, Philippe Talatchian +2
Superparamagnetic tunnel junctions (SMTJs) have emerged as a competitive, realistic nanotechnology to support novel forms of stochastic computation in CMOS-compatible platforms. On…