no code implementations • 4 Sep 2023 • Xiao-Yuan Wang, Jia-Wei Zhou, Chuan-Tao Dong, Xin-Hui Chen, Sanjoy Kumar Nandi, Robert G. Elliman, Sung-Mo Kang, Herbert Ho-Ching Iu
The design of balanced ternary digital logic circuits based on memristors and conventional CMOS devices is proposed.
no code implementations • 26 Jun 2022 • Peng Zhou, Jason K. Eshraghian, Dong-Uk Choi, Wei D. Lu, Sung-Mo Kang
We present MEMprop, the adoption of gradient-based learning to train fully memristive spiking neural networks (MSNNs).
no code implementations • 2 Mar 2022 • Peng Zhou, Jason K. Eshraghian, Dong-Uk Choi, Sung-Mo Kang
The natural spiking dynamics of the MIF neuron model are fully differentiable, eliminating the need for gradient approximations that are prevalent in the spiking neural network literature.
no code implementations • 2 Mar 2022 • Peng Zhou, Dong-Uk Choi, Jason K. Eshraghian, Sung-Mo Kang
We present a fully memristive spiking neural network (MSNN) consisting of physically-realizable memristive neurons and memristive synapses to implement an unsupervised Spiking Time Dependent Plasticity (STDP) learning rule.