This comprehensive review summarizes state of the art, challenges, and prospects of the
neuro-inspired computing with emerging nonvolatile memory devices. First, we discuss the …

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

This article provides a review of current development and challenges in brain-inspired
computing with memristors. We review the mechanisms of various memristive devices that …

Most memristor-based Pavlov associative memory neural networks strictly require that only
simultaneous food and ring appear to generate associative memory. In this article, the time …

Humanoid robots, intelligent machines resembling the human body in shape and functions,
cannot only replace humans to complete services and dangerous tasks but also deepen the …

Organic‐inorganic halide perovskites (OHPs) have been intensively studied for application
in solar cells with high conversion efficiency exceeding 22%. The unique electrical 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 …

The on-chip implementation of learning algorithms would speed up the training of neural
networks in crossbar arrays. The circuit level design and implementation of a back …

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 …

Artificial synapse having good linearity is crucial to achieve an efficient learning process in
neuromorphic computing. It is found that the synaptic linearity can be enhanced by …