With the exploration of ferroelectric materials, researchers have a strong desire to explore
the next generation of non‐volatile ferroelectric memory with silicon‐based epitaxy, high …

Ferroelectric memristors, as one of the most potential non-volatile memory to meet the rapid
development of the artificial intelligence era, have the comprehensive function of simulating …

Memristors that emulate synaptic plasticity are building blocks for opening a new era of
energy-efficient neuromorphic computing architecture, which will overcome the limitation of …

As a new type of nonvolatile memory, the resistive memristor has broad application
prospects in information storage and neural computing based on its excellent resistive …

We propose a hardware-friendly architecture of a convolutional neural network using a 32×
32 memristor crossbar array having an overshoot suppression layer. The gradual switching …

The synaptic properties of memristors have been widely studied. However, researchers are
still committed to solving various challenges, including the study of highly reliable …

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

Convolutional neural networks (CNNs) have been widely used in image recognition and
processing tasks. Memristor-based CNNs accumulate the advantages of emerging …

Recently, memristors with brain-like synaptic behavior have attracted widespread attention,
offering unprecedented opportunities for constructing future artificial intelligent bio-inspired …

Realization of memristor‐based neuromorphic hardware system is important to achieve
energy efficient bigdata processing and artificial intelligence in integrated device system …