The rapid development of information technology has led to urgent requirements for high
efficiency and ultralow power consumption. In the past few decades, neuromorphic …

This paper presents a comprehensive overview of modelling, simulation and implementation
of neural networks, taking into account that two aims have emerged in this area: the …

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 …

Neuromorphic computing provides alternative hardware architectures with high
computational efficiencies and low energy consumption by simulating the working principles …

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 …

Abstract The FitzHugh–Nagumo equation, originally conceived in neuroscience during the
1960s, became a key model providing a simplified view of excitable neuron cell behavior. Its …

The representation of external stimuli in the form of action potentials or spikes constitutes the
basis of energy efficient neural computation that emerging spiking neural networks (SNNs) …

BY combining neurophysiological principles with silicon engineering, we have produced an
analog integrated circuit with the functional characteristics of real nerve cells. Because the …

A silicon neuron circuit that produces spiking and bursting firing patterns, with biologically
plausible spike shape, is presented. The circuit mimics the behaviour of known classes of …

Written by more than 400 subject experts representing diverse academic and applied
domains, this multidisciplinary resource surveys the vanguard of biomaterials and …