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Condensed Matter > Mesoscale and Nanoscale Physics
Title: RF signal classification in hardware with an RF spintronic neural network
(Submitted on 2 Nov 2022 (this version), latest version 20 Apr 2023 (v2))
Abstract: Extracting information from radiofrequency (RF) signals using artificial neural networks at low energy cost is a critical need for a wide range of applications. Here we show how to leverage the intrinsic dynamics of spintronic nanodevices called magnetic tunnel junctions to process multiple analogue RF inputs in parallel and perform synaptic operations. Furthermore, we achieve classification of RF signals with experimental data from magnetic tunnel junctions as neurons and synapses, with the same accuracy as an equivalent software neural network. These results are a key step for embedded radiofrequency artificial intelligence.
Submission history
From: Alice Mizrahi [view email][v1] Wed, 2 Nov 2022 14:09:42 GMT (768kb)
[v2] Thu, 20 Apr 2023 12:10:00 GMT (1026kb)
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