176 citations · 176 across the 2 of their papers we have counts for
5 papers
Implementing a LoRa Software-Defined Radio on a General-Purpose ULP Microcontroller
Mathieu Xhonneux, Jérôme Louveaux, David Bol
Emerging Internet-of-Things sensing applications rely on ultra low-power (ULP) microcontroller units (MCUs) that wirelessly transmit data to the cloud. Typical MCUs nowadays consis…
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…
Learning without feedback: Fixed random learning signals allow for feedforward training of deep neural networks
Charlotte Frenkel, Martin Lefebvre, David Bol
While the backpropagation of error algorithm enables deep neural network training, it implies (i) bidirectional synaptic weight transport and (ii) update locking until the forward…
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…