The development of memristive device technologies has reached a level of...
Accurate detection of pathological conditions in human subjects can be
a...
The Lobula Giant Movement Detector (LGMD) is an identified neuron of the...
Neuromorphic hardware platforms implement biological neurons and synapse...
Neuromorphic systems typically use the Address-Event Representation (AER...
The increasing difficulty with Moore's law scaling and the remarkable su...
The increasing need for intelligent sensors in a wide range of everyday
...
Artificial neural networks and computational neuroscience models have ma...
Neuromorphic engineering (NE) encompasses a diverse range of approaches ...
Neuromorphic computing systems comprise networks of neurons that use
asy...
The Lobula Giant Movement Detector (LGMD) is a an identified neuron of t...
Despite their advantages in terms of computational resources, latency, a...
There is an urgent need for compact, fast, and power-efficient hardware
...
Many networks used in machine learning and as models of biological neura...
Solving constraint satisfaction problems (CSPs) is a notoriously expensi...
A striking difference between brain-inspired neuromorphic processors and...
Neural network algorithms simulated on standard computing platforms typi...