Since research on artificial intelligence has begun receiving much attention, interest in
efficient hardware that can process a complex and large amount of information has also …

Costly data movement in terms of time and energy in traditional von Neumann systems is
exacerbated by emerging information technologies related to artificial intelligence. In …

Recently, various resistance-based memory devices are being studied to replace charge-
based memory devices to satisfy high-performance memory requirements. Resistance …

Given the limitations of von Neumann computing systems, we propose a high-performance
reservoir computing system as an alternative. These systems operate as neural networks …

Artificial neural network-based computing prospectively overcomes the von Neumann
bottleneck of conventional computers and significantly improves computational efficiency …

We investigated the short-term memory characteristics of n-type-ZnO/p-type-NiO
heterojunction-based memristor devices to achieve a reservoir computing system. The …

This work presents the resistive switching characteristics of the TaO x-based conductive-
bridge random-access memory (CBRAM) for neuromorphic engineering. Controlling the Cu …

Neuromorphic computing, composed of artificial synapses and neural network algorithms, is
expected to replace the traditional von Neumann computer architecture to build the next …

In this work, ITO/ZTO/ITO transparent resistive memory was fabricated using a fully
industrialized sputtering process. We investigate how the electrical properties correspond to …

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