Search Results for author: Jean Anne C. Incorvia

Found 9 papers, 0 papers with code

Stochastic Domain Wall-Magnetic Tunnel Junction Artificial Neurons for Noise-Resilient Spiking Neural Networks

no code implementations10 Apr 2023 Thomas Leonard, Samuel Liu, Harrison Jin, Jean Anne C. Incorvia

The spatiotemporal nature of neuronal behavior in spiking neural networks (SNNs) make SNNs promising for edge applications that require high energy efficiency.

Shape-Dependent Multi-Weight Magnetic Artificial Synapses for Neuromorphic Computing

no code implementations22 Nov 2021 Thomas Leonard, Samuel Liu, Mahshid Alamdar, Can Cui, Otitoaleke G. Akinola, Lin Xue, T. Patrick Xiao, Joseph S. Friedman, Matthew J. Marinella, Christopher H. Bennett, Jean Anne C. Incorvia

In neuromorphic computing, artificial synapses provide a multi-weight conductance state that is set based on inputs from neurons, analogous to the brain.

Controllable reset behavior in domain wall-magnetic tunnel junction artificial neurons for task-adaptable computation

no code implementations8 Jan 2021 Samuel Liu, Christopher H. Bennett, Joseph S. Friedman, Matthew J. Marinella, David Paydarfar, Jean Anne C. Incorvia

Neuromorphic computing with spintronic devices has been of interest due to the limitations of CMOS-driven von Neumann computing.

Mesoscale and Nanoscale Physics

Domain Wall Leaky Integrate-and-Fire Neurons with Shape-Based Configurable Activation Functions

no code implementations11 Nov 2020 Wesley H. Brigner, Naimul Hassan, Xuan Hu, Christopher H. Bennett, Felipe Garcia-Sanchez, Can Cui, Alvaro Velasquez, Matthew J. Marinella, Jean Anne C. Incorvia, Joseph S. Friedman

This work proposes modifications to these spintronic neurons that enable configuration of the activation functions through control of the shape of a magnetic domain wall track.

CMOS-Free Multilayer Perceptron Enabled by Four-Terminal MTJ Device

no code implementations3 Feb 2020 Wesley H. Brigner, Naimul Hassan, Xuan Hu, Christopher H. Bennett, Felipe Garcia-Sanchez, Matthew J. Marinella, Jean Anne C. Incorvia, Joseph S. Friedman

Neuromorphic computing promises revolutionary improvements over conventional systems for applications that process unstructured information.

Exploiting Dual-Gate Ambipolar CNFETs for Scalable Machine Learning Classification

no code implementations9 Dec 2019 Farid Kenarangi, Xuan Hu, Yihan Liu, Jean Anne C. Incorvia, Joseph S. Friedman, Inna Partin-Vaisband

Ambipolar carbon nanotube based field-effect transistors (AP-CNFETs) exhibit unique electrical characteristics, such as tri-state operation and bi-directionality, enabling systems with complex and reconfigurable computing.

BIG-bench Machine Learning Classification +1

Cannot find the paper you are looking for? You can Submit a new open access paper.