Dense crossbar arrays of non-volatile memory (NVM) devices represent one possible path
for implementing massively-parallel and highly energy-efficient neuromorphic computing …

Memory cells have always been an important element of information technology. With
emerging technologies like big data and cloud computing, the scale and complexity of data …

The volume, veracity, variability, and velocity of data produced from the ever increasing
network of sensors connected to Internet pose challenges for power management …

In an increasingly data-rich world the need for developing computing systems that cannot
only process, but ideally also interpret big data is becoming continuously more pressing …

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 …

Memristors are promising components for applications in nonvolatile memory, logic circuits,
and neuromorphic computing. In this paper, a novel circuit for memristor-based multilayer …

忆阻器是除电阻, 电容, 电感之外发现的第4 种基本电子元件, 它是一种具有记忆特性的非线性
器件, 可用于混沌, 存储器, 神经网络等电路与系统的实现. 该文对基于忆阻器的混沌电路 …

As a promising alternative for next-generation memory, memristors provide several useful
features such as high density, nonvolatility, low power, and good scalability as compared …

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

Growth of data eases the way to access the world but requires increasing amounts of energy
to store and process. Neuromorphic electronics has emerged in the last decade, inspired by …