To realize highly efficient neuromorphic computing that is comparable to biological
counterparts, bioinspired computing systems, consisting of biorealistic artificial synapses …

The von Neumann bottleneck and memory wall have posed fundamental limitations in
latency and energy consumption of modern computers based on von Neumann architecture …

Memristors as electronic artificial synapses have attracted increasing attention in
neuromorphic computing. Emulation of both “learning” and “forgetting” processes requires a …

Recently, several types of lead halide perovskites have been demonstrated as active layers
in resistive switching memory or artificial synaptic devices for neuromorphic computing …

The electrical properties, resistive switching behavior, and long-term potentiation/depression
(LTP/LTD) in a single indium-gallium-zinc-oxide (IGZO) and bi-layer IGZO/ZnO (ZnO: zinc …

With the advancement of artificial intelligence technology, more and more biological
functions need to be imitated to complete more complex tasks and adapt to a complex …

As artificial synapses in biomimetics, memristors have received increasing attention
because of their great potential in brain-inspired neuromorphic computing. The use of …

As the era of big data approaches, conventional digital computers face increasing difficulties
in performance and power efficiency due to their von Neumann architecture. As a result …

Neural networks, one of the key artificial intelligence technologies today, have the
computational power and learning ability similar to the brain. However, implementation of …

Physically transient electronic devices that can disappear on demand have great application
prospects in the field of information security, implantable biomedical systems, and …