Demonstration of combining Resonate-and-Fire (RF) neurons and unsupervised hebbian learning to build a SNN capable of recognizing (complex) patterns in time data.
Neuromorphic Wireless Split Computing with Resonate-and-Fire Neurons
Partial reproduction of Balanced-Resonate-And-Fire (BRF) neurons by Higuchi et al. Extension by experimentation on decay functions, energy aware loss, and Google Speech Commands dataset with BRF neurons.
Resonate-and-fire neuron model enabled for backpropagation learning with PyTorch
Generates a synthetic control dataset of spike trains designed to test exploding spiking behavior in Resonate-and-Fire (RF) neurons (Izhikevich, 2001).
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