10 citations · 19 across the 4 of their papers we have counts for
3 papers · 1 filter
Learning and Inferring Relations in Cortical Networks
Peter U. Diehl, Matthew Cook
A pressing scientific challenge is to understand how brains work. Of particular interest is the neocortex,the part of the brain that is especially large in humans, capable of handl…
Conversion of Artificial Recurrent Neural Networks to Spiking Neural Networks for Low-power Neuromorphic Hardware
Peter U. Diehl, Guido Zarrella, Andrew Cassidy +2
In recent years the field of neuromorphic low-power systems that consume orders of magnitude less power gained significant momentum. However, their wider use is still hindered by t…
TrueHappiness: Neuromorphic Emotion Recognition on TrueNorth
Peter U. Diehl, Bruno U. Pedroni, Andrew Cassidy +3
We present an approach to constructing a neuromorphic device that responds to language input by producing neuron spikes in proportion to the strength of the appropriate positive or…