Memristive technology has been rapidly emerging as a potential alternative to traditional
CMOS technology, which is facing fundamental limitations in its development. Since oxide …

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 …

Abstract We developed W/HfO 2/TiN vertical resistive random-access memory (VRRAM) for
neuromorphic computing. First, basic electrical properties, such as current–voltage curves …

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 …

We propose a hardware-friendly architecture of a convolutional neural network using a 32×
32 memristor crossbar array having an overshoot suppression layer. The gradual switching …

The progress of artificial intelligence and the development of large‐scale neural networks
have significantly increased computational costs and energy consumption. To address these …

Recently, various memory devices have been actively studied as suitable candidates for
synaptic devices, which are important memory and computing units in neuromorphic …

In this work, we present a hardware neural network with capacitor-based synaptic devices. A
capacitor-based synaptic device was developed using a MOS capacitor structure with a …

In this study, we evaluate the performance of a physical unclonable function (PUF) using Al
2 O 3/TiO x based memristors. Through a conduction mechanism analysis, it is confirmed …