In the past few decades, NAND flash memory has been one of the most successful
nonvolatile storage technologies, and it is commonly used in electronic devices because of …

Neuromorphic computing has emerged as one of the most promising paradigms to
overcome the limitations of von Neumann architecture of conventional digital processors …

The rapid development of neuro-inspired computing demands synaptic devices with ultrafast
speed, low power consumption, and multiple non-volatile states, among other features …

Neuromorphic computing based on spikes offers great potential in highly efficient computing
paradigms. Recently, several hardware implementations of spiking neural networks based …

Neuromorphic computing is henceforth a major research field for both academic and
industrial actors. As opposed to Von Neumann machines, brain-inspired processors aim at …

This work presents 2-bits/cell operation in deeply scaled ferroelectric finFETs (Fe-finFET)
with a 1 µs write pulse of maximum±5 V amplitude and WRITE endurance above 109 cycles …

To apply resistive random‐access memory (RRAM) to the neuromorphic system and
improve performance, each cell in the array should be able to operate independently by …

Multilevel operation is one of the most essential properties for synaptic devices to realize
hardware artificial neural networks. Compliance current (I cc) adjustment is a multilevel …

This paper reports 2bits/cell ferroelectric FET (FeFET) devices with 500 ns write pulse of
maximum amplitude 4.5 V for inference-engine applications. FeFET devices were fabricated …

In recent years, photoelectronic synaptic devices have emerged as a platform for use in next-
generation neuromorphic systems and artificial neural networks (ANNs). In this paper, we …