21 citations · 49 across the 4 of their papers we have counts for
4 papers
Expanding memory in recurrent spiking networks
Ismael Balafrej, Fabien Alibart, Jean Rouat
Recurrent spiking neural networks (RSNNs) are notoriously difficult to train because of the vanishing gradient problem that is enhanced by the binary nature of the spikes. In this…
Voltage-Dependent Synaptic Plasticity (VDSP): Unsupervised probabilistic Hebbian plasticity rule based on neurons membrane potential
Nikhil Garg, Ismael Balafrej, Terrence C. Stewart +7
This study proposes voltage-dependent-synaptic plasticity (VDSP), a novel brain-inspired unsupervised local learning rule for the online implementation of Hebb's plasticity mechani…
Signals to Spikes for Neuromorphic Regulated Reservoir Computing and EMG Hand Gesture Recognition
Nikhil Garg, Ismael Balafrej, Yann Beilliard +3
Surface electromyogram (sEMG) signals result from muscle movement and hence they are an ideal candidate for benchmarking event-driven sensing and computing. We propose a simple yet…
P-CRITICAL: A Reservoir Autoregulation Plasticity Rule for Neuromorphic Hardware
Ismael Balafrej, Jean Rouat
Backpropagation algorithms on recurrent artificial neural networks require an unfolding of accumulated states over time. These states must be kept in memory for an undefined period…