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Physical reservoir computing built by spintronic devices for temporal info proc (arxiv.org)
1 point by godelmachine on Jan 25, 2019 | hide | past | pdf | discuss on HN

In plain words: Tiny magnetic devices that switch in complex ways when zapped with current act as a built-in memory brain, turning past inputs into rich signals instead of a software neural network. One such device recognized handwritten digits well, and 24 of them predicted changing systems.

Abstract · Physical reservoir computing built by spintronic devices for temporal information processing

Spintronic nanodevices have ultrafast nonlinear dynamic and recurrence behaviors on a nanosecond scale that promises to enable spintronic reservoir computing (RC) system. Here two physical RC systems based on a single magnetic skyrmion memristor (MSM) and 24 spin-torque nano-oscillators (STNOs) were proposed and modeled to process image classification task and nonlinear dynamic system prediction, respectively. Based on our micromagnetic simulation results on the nonlinear responses of MSM and STNO with current pulses stimulation, the handwritten digits recognition task domesticates that an RC system using one single MSM has the outstanding performance on image classification. In addition, the complex unknown nonlinear dynamic problems can also be well solved by a physical RC system consisted of 24 STNOs confirmed in a second-order nonlinear dynamic system and NARMA10 tasks. The capability of both high accuracy and fast information processing promises to enable one type of brain-like chip based on spintronics for various artificial intelligence tasks.

Wencong Jiang, Lina Chen, Kaiyuan Zhou, Liyuan Li, Qingwei Fu, Youwei Du, Ronghua Liu
arXiv:1901.07879 · cs.ET, physics.app-ph · submitted Jan 23, 2019 · updated Mar 29, 2019
abstract · pdf · html · 7 pages, 6 figures

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