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.
|Original language||English (US)|
|Number of pages||9|
|Journal||IEEE Journal on Exploratory Solid-State Computational Devices and Circuits|
|State||Published - Jun 2019|
Bibliographical notePublisher Copyright:
© 2014 IEEE.
- Cellular neural network (CNN)
- energy efficiency
- magnetoelectric (ME)