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Riou M, Torrejon J, Garitaine B, et al. Temporal pattern recognition with delayed feedback spin-torque nano-oscillators. Phys Rev Appl. 2019;12(2)doi: 10.1103/physrevapplied.12.024049.
Riou, M., Torrejon, J., Garitaine, B., Araujo, F. A., Bortolotti, P., Cros, V., Tsunegi, S., Yakushiji, K., Fukushima, A., Kubota, H., Yuasa, S., Querlioz, D., Stiles, M. D., & Grollier, J. (2019). Temporal pattern recognition with delayed feedback spin-torque nano-oscillators. Physical review applied, 12(2), . https://doi.org/10.1103/physrevapplied.12.024049
Riou, M, et al. "Temporal pattern recognition with delayed feedback spin-torque nano-oscillators." Physical review applied vol. 12,2 (2019). doi: https://doi.org/10.1103/physrevapplied.12.024049
Riou M, Torrejon J, Garitaine B, Araujo FA, Bortolotti P, Cros V, Tsunegi S, Yakushiji K, Fukushima A, Kubota H, Yuasa S, Querlioz D, Stiles MD, Grollier J. Temporal pattern recognition with delayed feedback spin-torque nano-oscillators. Phys Rev Appl. 2019;12(2). doi: 10.1103/physrevapplied.12.024049. PMID: 32118096; PMCID: PMC7047780.
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Phys Rev Appl. 2019;12(2). doi: 10.1103/physrevapplied.12.024049.

Temporal pattern recognition with delayed feedback spin-torque nano-oscillators.

Physical review applied

M Riou, J Torrejon, B Garitaine, F Abreu Araujo, P Bortolotti, V Cros, S Tsunegi, K Yakushiji, A Fukushima, H Kubota, S Yuasa, D Querlioz, M D Stiles, J Grollier

Affiliations

  1. Unité Mixte de Physique CNRS, Thales,Université Paris-Sud, Université Paris-Saclay, 91767 Palaiseau, France.
  2. National Institute of Advanced Industrial Science and Technology (AIST), Spintronic Research Center, Tsukuba, Ibaraki 305-8568, Japan.
  3. Center for Nanoscience and Nanotechnology, CNRS, Université Paris-Sud, Université Paris-Saclay, 91405, Orsay, France.
  4. Center for Nanoscale Science and Technology, National Institute of Standards and Technology, Gaithersburg, Maryland 20899-6202, USA.

PMID: 32118096 PMCID: PMC7047780 DOI: 10.1103/physrevapplied.12.024049

Abstract

The recent demonstration of neuromorphic computing with spin-torque nano-oscillators has opened a path to energy efficient data processing. The success of this demonstration hinged on the intrinsic short-term memory of the oscillators. In this study, we extend the memory of the spin-torque nano-oscillators through time-delayed feedback. We leverage this extrinsic memory to increase the efficiency of solving pattern recognition tasks that require memory to discriminate different inputs. The large tunability of these non-linear oscillators allows us to control and optimize the delayed feedback memory using different operating conditions of applied current and magnetic field.

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