Tunable Stochasticity in an Artificial Spin Network-Reference-Cited by-同舟云学术

Tunable Stochasticity in an Artificial Spin Network

Published:2021-03-18 Issue:17 Volume:33 Page:2008135
ISSN:0935-9648
Container-title:Advanced Materials
language:en
Short-container-title:Adv. Mater.

Author:

Sanz‐Hernández Dédalo¹^ORCID,Massouras Maryam²^ORCID,Reyren Nicolas¹^ORCID,Rougemaille Nicolas³^ORCID,Schánilec Vojtěch⁴^ORCID,Bouzehouane Karim¹^ORCID,Hehn Michel²^ORCID,Canals Benjamin³,Querlioz Damien⁵^ORCID,Grollier Julie¹^ORCID,Montaigne François²^ORCID,Lacour Daniel²^ORCID

Affiliation:

1. Unité Mixte de Physique, CNRS, Thales Université Paris‐Saclay Palaiseau 91767 France

2. Université de Lorraine, CNRS Institut Jean Lamour Nancy F‐54000 France

3. Université Grenoble Alpes, CNRS, Grenoble INP Institut NEEL Grenoble 38000 France

4. Central European Institute of Technology Brno University of Technology Brno 61200 Czech Republic

5. Université Paris‐Saclay, CNRS Centre de Nanosciences et de Nanotechnologies Palaiseau 91120 France

Funder

Agence Nationale de la Recherche

Publisher

Wiley

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/adma.202008135

Reference33 articles.

1. There’s plenty of room at the Top: What will drive computer performance after Moore’s law?

2. A million spiking-neuron integrated circuit with a scalable communication network and interface

3. Training and operation of an integrated neuromorphic network based on metal-oxide memristors

4. Neuromorphic computing with nanoscale spintronic oscillators

5. Equivalent-accuracy accelerated neural-network training using analogue memory

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