Braindrop is the first neuromorphic system designed to be programmed at a high level of
abstraction. Previous neuromorphic systems were programmed at the neurosynaptic level …

Brain-inspired computing uses insights from neuroscience to develop more efficient
computing systems. The approach is of use in a broad range of applications—from neural …

Dynamical systems are universal computers. They can perceive stimuli, remember, learn
from feedback, plan sequences of actions, and coordinate complex behavioural responses …

To convert a subthreshold current to a pulse frequency efficiently and predictably, we
designed a silicon soma that conserves energy with current feedback and lessens thermal …

Perceptron is an essential element in neural network (NN)-based machine learning,
however, the effectiveness of various implementations by circuits is rarely demonstrated …

The explosive growth in semiconductor integrated circuits was made possible in large part
by design automation software. The design and/or analysis of synthetic and natural circuits …

We present Polynomial in Temperature (PinT) decode weights, a novel approach to
approximating functions with an ensemble of silicon neurons that increases thermal …

Mathematical models are used widely throughout the sciences, and often influence not only
research, but our daily lives. For example, weather prediction is made possible by numerical …

La present tesi recull els resultats de la recerca orientada a aportar una metodologia de
caracterització elèctrica, modelat i simulació per a dispositius de commutació resistiva, quan …