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Performance Estimate of Inverse Rashba-Edelstein Magnetoelectric Devices for Neuromorphic Computing

IEEE Journal on Exploratory Solid-State Computational Devices and Circuits (2019) 5(1) 25-33
DOI: 10.1109/JXCDC.2019.2903286
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Abstract

We propose a new design for a cellular neural network with spintronic neurons and CMOS-based synapses. Harnessing the magnetoelectric and inverse Rashba-Edelstein effects allows natural emulation of the behavior of an ideal cellular network. This combination of effects offers an increase in speed and efficiency over other spintronic neural networks. A rigorous performance analysis via simulation is provided.

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Stephan, A. W., Hu, J., & Koester, S. J. (2019). Performance Estimate of Inverse Rashba-Edelstein Magnetoelectric Devices for Neuromorphic Computing. IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 5(1), 25–33. https://doi.org/10.1109/JXCDC.2019.2903286

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