176 citations · 176 across the 2 of their papers we have counts for
3 papers
A 28-nm Convolutional Neuromorphic Processor Enabling Online Learning with Spike-Based Retinas
Charlotte Frenkel, Jean-Didier Legat, David Bol
In an attempt to follow biological information representation and organization principles, the field of neuromorphic engineering is usually approached bottom-up, from the biophysic…
MorphIC: A 65-nm 738k-Synapse/mm Quad-Core Binary-Weight Digital Neuromorphic Processor with Stochastic Spike-Driven Online Learning
Charlotte Frenkel, Jean-Didier Legat, David Bol
Recent trends in the field of neural network accelerators investigate weight quantization as a means to increase the resource- and power-efficiency of hardware devices. As full on-…
A 0.086-mm 12.7-pJ/SOP 64k-Synapse 256-Neuron Online-Learning Digital Spiking Neuromorphic Processor in 28nm CMOS
Charlotte Frenkel, Martin Lefebvre, Jean-Didier Legat +1
Shifting computing architectures from von Neumann to event-based spiking neural networks (SNNs) uncovers new opportunities for low-power processing of sensory data in applications…