The demand for computing power has been increasing exponentially since the emergence
of artificial intelligence (AI), internet of things (IoT), and machine learning (ML), where novel …

Simulating biological synaptic functionalities through artificial synaptic devices opens up an
innovative way to overcome the von Neumann bottleneck at the device level. Artificial …

Neuromorphic architectures are in the spotlight as promising candidates for substituting
current computing systems owing to their high operation speed, scale‐down ability, and …

Compared with the traditional von Neumann architecture, neural systems have many
distinctive properties including parallelism, low-power consumption, fault tolerance, self …

Human brain outperforms the current von Neumann digital computer in many aspects, such
as energy efficiency and fault‐tolerance. Inspired by human brain, neuromorphic …

The traditional von Neumann structure computers cannot meet the demands of high-speed
big data processing; therefore, neuromorphic computing has received a lot of interest in …

In recent years, the emergence of memory devices, especially resistive random-access
memories (RRAM), has been a front-runner in many technological applications. This is due …

Oscillatory Neural Networks (ONNs) are currently arousing interest in the research
community for their potential to implement very fast, ultra-low-power computing tasks by …

A 3 CNFETs and 2 memristors-based half-select disturbance free 3T2R resistive RAM
(RRAM) cell is proposed in this paper. While the two memristors act as the nonvolatile …

Herein, excellent non-volatile memory and aqueous battery properties of solution-
processable nickel ferrite (NFO) nanomaterial were demonstrated. In the case of non-volatile …