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20212023
most citedLogical and Physical Reversibility of Conservative Skyrmion Logic

3 citations · 15 across the 7 of their papers we have counts for

collaborators

7 papers

cond-mat.mtrl-sci2023★ 2 cited

Cascaded Logic Gates Based on High-Performance Ambipolar Dual-Gate WSe2 Thin Film Transistors

Xintong Li, Peng Zhou, Xuan Hu +6

Ambipolar dual-gate transistors based on two-dimensional (2D) materials, such as graphene, carbon nanotubes, black phosphorus, and certain transition metal dichalcogenides (TMDs),…

cs.NE2022★ 3 cited

Gradient-based Neuromorphic Learning on Dynamical RRAM Arrays

Peng Zhou, Jason K. Eshraghian, Dong-Uk Choi +2

We present MEMprop, the adoption of gradient-based learning to train fully memristive spiking neural networks (MSNNs). Our approach harnesses intrinsic device dynamics to trigger n…

cs.ET2022★ 3 cited

Logical and Physical Reversibility of Conservative Skyrmion Logic

Xuan Hu, Benjamin W. Walker, Felipe García-Sánchez +6

Magnetic skyrmions are nanoscale whirls of magnetism that can be propagated with electrical currents. The repulsion between skyrmions inspires their use for reversible computing ba…

cs.NE2022★ 1 cited

SPICEprop: Backpropagating Errors Through Memristive Spiking Neural Networks

Peng Zhou, Jason K. Eshraghian, Dong-Uk Choi +1

We present a fully memristive spiking neural network (MSNN) consisting of novel memristive neurons trained using the backpropagation through time (BPTT) learning rule. Gradient des…

cs.NE2022★ 1 cited

A Fully Memristive Spiking Neural Network with Unsupervised Learning

Peng Zhou, Dong-Uk Choi, Jason K. Eshraghian +1

We present a fully memristive spiking neural network (MSNN) consisting of physically-realizable memristive neurons and memristive synapses to implement an unsupervised Spiking Time…

cs.NE2021★ 2 cited

Synchronous Unsupervised STDP Learning with Stochastic STT-MRAM Switching

Peng Zhou, Julie A. Smith, Laura Deremo +2

The use of analog resistance states for storing weights in neuromorphic systems is impeded by fabrication imprecision and device stochasticity that limit the precision of synapse w…

cs.NE2021★ 3 cited

Experimental Demonstration of Neuromorphic Network with STT MTJ Synapses

Peng Zhou, Alexander J. Edwards, Fred B. Mancoff +3

We present the first experimental demonstration of a neuromorphic network with magnetic tunnel junction (MTJ) synapses, which performs image recognition via vector-matrix multiplic…