The human brain is a sophisticated, high‐performance biocomputer that processes multiple
complex tasks in parallel with high efficiency and remarkably low power consumption …

Spiking neural networks (SNNs) are inspired by information processing in biology, where
sparse and asynchronous binary signals are communicated and processed in a massively …

The brain is the perfect place to look for inspiration to develop more efficient neural
networks. The inner workings of our synapses and neurons provide a glimpse at what the …

In recent years, deep learning has revolutionized the field of machine learning, for computer
vision in particular. In this approach, a deep (multilayer) artificial neural network (ANN) is …

Artificial neural networks have been used as a powerful processing tool in various areas
such as pattern recognition, control, robotics, and bioinformatics. Their wide applicability has …

As a new brain-inspired computational model of the artificial neural network, a spiking
neural network encodes and processes neural information through precisely timed spike …

A vast majority of computation in the brain is performed by spiking neural networks. Despite
the ubiquity of such spiking, we currently lack an understanding of how biological spiking …

Spiking neural networks (SNNs) are well suited for spatio-temporal learning and
implementations on energy-efficient event-driven neuromorphic processors. However …

We propose a spiking neural network model that encodes information in the relative timing
of individual neuron spikes and performs classification using the first output neuron to spike …

The memristor is a resistive switch where its resistive state is programable based on the
applied voltage or current. Memristive devices are thus capable of storing and computing …