The volume, veracity, variability, and velocity of data produced from the ever increasing
network of sensors connected to Internet pose challenges for power management …

Inspired by biology, neuromorphic systems have been trying to emulate the human brain for
decades, taking advantage of its massive parallelism and sparse information coding …

Recent theoretical studies have shown that probabilistic spiking can be interpreted as
learning and inference in cortical microcircuits. This interpretation creates new opportunities …

In order to map the computing architecture and intelligent functions of the human brain on
hardware, we need electronic devices that can emulate biological synapses and even …

Brain-inspired neuromorphic systems have attracted much attention as new computing
paradigms for power-efficient computation. Here, we report a silicon synaptic transistor with …

Nanoelectronic devices that mimic the functionality of synapses are a crucial requirement for
performing cortical simulations of the brain. In this work, we propose a ferromagnet-heavy …

Synaptic memristor has attracted much attention for its potential applications in artificial
neural networks (ANNs). However useful applications in real life with such memristor-based …

A device based on current-induced spin-orbit torque (SOT) that functions as an electronic
neuron is proposed in this work. The SOT device implements an artificial neuron's …

A hardware based artificial neural network (ANN), which holds the potential to alleviate the
computation load and energy of a digital computer, has propelled the development of …

Over the last 11 years, the field of Memristive Sensors abruptly emerged in literature. The
present review paper has the aim to acknowledge such an exciting new field of research as …