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Displaying 1 - 6 of 6

Self-training neuromorphic circuits using reinforcement learning rules

March 4, 2025
Author(s)
Matthew Pufall, Emilie Jue, Chuck Anderson, Ken Segall, Michael Schneider
Neuromorphic computing takes biological inspiration to the device level aiming to improve computational efficiency and capabilities. One of the major issues that arises is the training of neuromorphic hardware systems. Typically training algorithms require

Mutual control of stochastic switching for two electrically coupled superparamagnetic tunnel junctions

August 19, 2021
Author(s)
Philippe Talatchian, Matthew Daniels, Advait Madhavan, Matthew Pufall, Emilie Jue, William Rippard, Jabez J. McClelland, Mark Stiles
Superparamagnetic tunnel junctions (SMTJs) are promising sources for the randomness required by some compact and energy-efficient computing schemes. Coupling them gives rise to collective behavior that could be useful for cognitive computing. We use a

Asymmetric and partial injection locking of a three-terminal spin-torque oscillator

March 9, 2018
Author(s)
Emilie M. Jue, Matthew R. Pufall, William H. Rippard
We measure the injection locking of a three-terminal spin-torque oscillator (STO) excited by a spin-orbit torque. The device consists of a magnetic tunnel junction on top of a Pt wire. A DC and an AC current are applied through the Pt wire to respectively
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