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 …

Ambipolar transistors represent a class of transistors where positive (holes) and negative
(electrons) charge carriers both can transport concurrently within the semiconducting …

Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices,
and models that contrast the pervasive von Neumann computer architecture. This …

Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning
(DL) is already present in many applications ranging from computer vision for medicine to …

DOI: 10.1002/adma. 201502719 memory functions concurrently because voltage spike
applied on the gate electrode can modulate the channel conductance between the source …

Several analog and digital brain-inspired electronic systems have been recently proposed
as dedicated solutions for fast simulations of spiking neural networks. While these …

The multilevel capability of metal oxide resistive switching memory was explored for the
potential use as a single-element electronic synapse device. TiN/HfO x/AlO x/Pt resistive …

Memristors have been proposed for a number of applications from nonvolatile memory to
neuromorphic systems. Unlike conventional devices based solely on electron transport …

Hardware implementations of spiking neurons can be extremely useful for a large variety of
applications, ranging from high-speed modeling of large-scale neural systems to real-time …

Neurons in the brain communicate by short electrical pulses, the so-called action potentials
or spikes. How can we understand the process of spike generation? How can we …