Neuromorphic computing takes inspiration from the brain to create energy-efficient hardware
for information processing, capable of highly sophisticated tasks. Systems built with standard …

Neuromorphic Computing, a concept pioneered in the late 1980s, is receiving a lot of
attention lately due to its promise of reducing the computational energy, latency, as well as …

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

In this article, we review the recent progress of ferroelectric field-effect transistors (FeFETs)
based on ferroelectric hafnium oxide (HfO 2), ten years after the first report on such a device …

Dense crossbar arrays of non-volatile memory (NVM) devices represent one possible path
for implementing massively-parallel and highly energy-efficient neuromorphic computing …

Bioinspired hardware holds the promise of low-energy, intelligent, and highly adaptable
computing systems. Applications span from automatic classification for big data …

In an increasingly data-rich world the need for develo** computing systems that cannot
only process, but ideally also interpret big data is becoming continuously more pressing …

Brain-inspired neuromorphic computing is expected to revolutionize the architecture of
conventional digital computers and lead to a new generation of powerful computing …

Memristors are non-volatile nano-resistors which resistance can be tuned by applied
currents or voltages and set to a large number of levels. Thanks to these properties …

We present a novel one-transistor/one-resistor (1T1R) synapse for neuromorphic networks,
based on phase change memory (PCM) technology. The synapse is capable of spike-timing …