3 citations · 4 across the 6 of their papers we have counts for
7 papers
Biologically Realistic Dynamics for Nonlinear Classification in CMOS+X Neurons
Steven Louis, Hannah Bradley, Artem Litvinenko +3
Spiking neural networks encode information in spike timing and offer a pathway toward energy efficient artificial intelligence. However, a key challenge in spiking neural networks…
A CMOS+X Spiking Neuron With On-Chip Machine Learning
Steven Louis, Matthew Blake Abramson, Hannah Bradley +8
We present the design and numerical simulation of a spiking neuron in a proof-of-concept model of on-chip machine learning. Built within the CMOS+X framework, the spiking neuron co…
A Physics-Based Circuit Model for Magnetic Tunnel Junctions
Steven Louis, Hannah Bradley, Artem Litvinenko +1
This work presents an equivalent circuit model for Magnetic Tunnel Junctions (MTJs) that accurately captures their magnetization dynamics and electrical behavior. Implemented in LT…
Equivalent Electric Model of a Macrospin
Steven Louis, Hannah Bradley, Vasyl Tyberkevych
Dynamics of a ferromagnetic macrospin (e.g., a free layer of a magnetic tunnel junction (MTJ)) can be described in terms of equivalent capacitor charge and inductor flux , i…
Spintronic Neuron Using a Magnetic Tunnel Junction for Low-Power Neuromorphic Computing
Steven Louis, Hannah Bradley, Cody Trevillian +2
This paper proposes a novel spiking artificial neuron design based on a combined spin valve/magnetic tunnel junction (SV/MTJ). Traditional hardware used in artificial intelligence…
Pattern recognition using spiking antiferromagnetic neurons
Hannah Bradley, Steven Louis, Andrei Slavin +1
Spintronic devices offer a promising avenue for the development of nanoscale, energy-efficient artificial neurons for neuromorphic computing. It has previously been shown that with…
Artificial neurons based on antiferromagnetic auto-oscillators as a platform for neuromorphic computing
Hannah Bradley, Steven Louis, Cody Trevillian +4
Spiking artificial neurons emulate the voltage spikes of biological neurons, and constitute the building blocks of a new class of energy efficient, neuromorphic computing systems.…