3 citations · 15 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
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…
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…
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…