The rapid development of information technology has led to urgent requirements for high
efficiency and ultralow power consumption. In the past few decades, neuromorphic …

Artificial neuronal devices are critical building blocks of neuromorphic computing systems
and currently the subject of intense research motivated by application needs from new …

We report on switching dynamics of individual and coupled vanadium dioxide (VO 2)
devices subject to voltage pulses as the temperature is systematically varied from room …

The neural network enables efficient solutions for Nondeterministic Polynomial-time (NP)
hard problems, which are challenging for conventional von Neumann computing. The …

This work demonstrates oscillation frequency modulation in a NbO 2-based relaxation
oscillator device, in which the oscillation frequency increases with operating temperature …

Neural Networks have long been a mainstream technique to solve optimization problems. A
classic example is the Travelling Salesman Problem (TSP) which NP-hard. Using a Hopfield …

Manganite based Resistance Random Access Memories (RRAM) are attractive as they are
non-volatile, area-scalable, with fast switching and large endurance and retention. However …

Memristors, or more generally “memristive systems,” are nonlinear electric components that
change their resistance depending on a set of state variables. Meanwhile, negative …

Oscillatory Neural Networks (ONNs) have been reported to solve graphical constraint
optimization and pattern recognition problems in a time efficient manner [1],[2]. In particular …

This article is an overview of emerging memory materials and their role in advanced brain-
inspired computing technologies. It starts with the progress of memory technologies over the …