Guided by brain-like 'spiking'computational frameworks, neuromorphic computing—brain-
inspired computing for machine intelligence—promises to realize artificial intelligence while …

Modern computers are based on the von Neumann architecture in which computation and
storage are physically separated: data are fetched from the memory unit, shuttled to the …

This article presents a review of the current development and challenges in memristor
modeling. We review the mechanisms of memristive devices based on various …

Resistive random access memory (RRAM) devices are receiving increasing extensive
attention due to their enhanced properties such as fast operation speed, simple device …

Resistive memories are outstanding electron devices that have displayed a large potential in
a plethora of applications such as nonvolatile data storage, neuromorphic computing …

Resistive memory technologies could be used to create intelligent systems that learn locally
at the edge. However, current approaches typically use learning algorithms that cannot be …

With the explosive growth of digital data in the era of the Internet of Things (IoT), fast and
scalable memory technologies are being researched for data storage and data-driven …

As complementary metal–oxide–semiconductor (CMOS) scaling reaches its technological
limits, a radical departure from traditional von Neumann systems, which involve separate …

Silver/copper-filament-based resistive switching memory relies on the formation and
disruption of a metallic conductive filament (CF) with relatively large surface-to-volume ratio …

In-memory computing (IMC) has emerged as a new computing paradigm able to alleviate or
suppress the memory bottleneck, which is the major concern for energy efficiency and …