Recent advances and future prospects for memristive materials, devices, and systems
Memristive technology has been rapidly emerging as a potential alternative to traditional
CMOS technology, which is facing fundamental limitations in its development. Since oxide …
CMOS technology, which is facing fundamental limitations in its development. Since oxide …
Understanding memristive switching via in situ characterization and device modeling
Owing to their attractive application potentials in both non-volatile memory and
unconventional computing, memristive devices have drawn substantial research attention in …
unconventional computing, memristive devices have drawn substantial research attention in …
Fully hardware-implemented memristor convolutional neural network
Memristor-enabled neuromorphic computing systems provide a fast and energy-efficient
approach to training neural networks,,–. However, convolutional neural networks (CNNs) …
approach to training neural networks,,–. However, convolutional neural networks (CNNs) …
Open-loop analog programmable electrochemical memory array
P Chen, F Liu, P Lin, P Li, Y **ao, B Zhang… - Nature …, 2023 - nature.com
Emerging memories have been developed as new physical infrastructures for hosting neural
networks owing to their low-power analog computing characteristics. However, accurately …
networks owing to their low-power analog computing characteristics. However, accurately …
Memristor-based analogue computing for brain-inspired sound localization with in situ training
The human nervous system senses the physical world in an analogue but efficient way. As a
crucial ability of the human brain, sound localization is a representative analogue computing …
crucial ability of the human brain, sound localization is a representative analogue computing …
Analog memristive synapse based on topotactic phase transition for high-performance neuromorphic computing and neural network pruning
Inspired by the human brain, nonvolatile memories (NVMs)–based neuromorphic computing
emerges as a promising paradigm to build power-efficient computing hardware for artificial …
emerges as a promising paradigm to build power-efficient computing hardware for artificial …
Concealable physically unclonable function chip with a memristor array
A physically unclonable function (PUF) is a creditable and lightweight solution to the mistrust
in billions of Internet of Things devices. Because of this remarkable importance, PUF need to …
in billions of Internet of Things devices. Because of this remarkable importance, PUF need to …
In-memory learning with analog resistive switching memory: A review and perspective
In this article, we review the existing analog resistive switching memory (RSM) devices and
their hardware technologies for in-memory learning, as well as their challenges and …
their hardware technologies for in-memory learning, as well as their challenges and …
Device and materials requirements for neuromorphic computing
Energy efficient hardware implementation of artificial neural network is challenging due
the'memory-wall'bottleneck. Neuromorphic computing promises to address this challenge by …
the'memory-wall'bottleneck. Neuromorphic computing promises to address this challenge by …
From memristive materials to neural networks
The information technologies have been increasing exponentially following Moore's law
over the past decades. This has fundamentally changed the ways of work and life. However …
over the past decades. This has fundamentally changed the ways of work and life. However …