Edge computing is an emerging paradigm that offloads the computations and analytics
workloads onto the Internet of Things (IoT) edge devices to accelerate the computation …

With the booming growth of artificial intelligence (AI), the traditional von Neumann
computing architecture based on complementary metal oxide semiconductor devices are …

Bioinspired computation systems can achieve artificial intelligence, bypassing fundamental
bottlenecks and cost constraints. Computational frameworks suited for temporal/sequential …

Abstract Nanowire Networks (NWNs) belong to an emerging class of neuromorphic systems
that exploit the unique physical properties of nanostructured materials. In addition to their …

Neuromorphic computing based on memristors capable of in-memory computing is
promising to break the energy and efficiency bottleneck of well-known von Neumann …

A high‐density neuromorphic computing memristor array based on 2D materials paves the
way for next‐generation information‐processing components and in‐memory computing …

Reservoir computing (RC) is a computational architecture capable of efficiently processing
temporal information, which allows low-cost hardware implementation. However, the …

The imitation of human visual memory demands the multifunctional integration of light
sensors similar to the eyes, and image memory, similar to the brain. Although humans have …

Neuromorphic computing is a promising computing paradigm toward building next-
generation artificial intelligence machines, in which diverse types of synaptic plasticity play …

Physical reservoir computing is a form of neuromorphic computing that harvests the dynamic
properties of materials for high-efficiency computing. A wide range of physical systems can …