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

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-osci...

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Bibliographic Details
Published in:Physical review applied 2019-08, Vol.12 (2), Article 024049
Main Authors: Riou, M, Torrejon, J, Garitaine, B, Araujo, F Abreu, Bortolotti, P, Cros, V, Tsunegi, S, Yakushiji, K, Fukushima, A, Kubota, H, Yuasa, S, Querlioz, D, Stiles, M D, Grollier, J
Format: Article
Language:English
Subjects:
Condensed Matter
Nonlinear Sciences
Physics
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Summary: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.
ISSN:2331-7019
2331-7019
DOI:10.1103/PhysRevApplied.12.024049