Resistive switching materials for information processing
The rapid increase in information in the big-data era calls for changes to information-
processing paradigms, which, in turn, demand new circuit-building blocks to overcome the …
processing paradigms, which, in turn, demand new circuit-building blocks to overcome the …
A comprehensive review on emerging artificial neuromorphic devices
The rapid development of information technology has led to urgent requirements for high
efficiency and ultralow power consumption. In the past few decades, neuromorphic …
efficiency and ultralow power consumption. In the past few decades, neuromorphic …
Bridging biological and artificial neural networks with emerging neuromorphic devices: fundamentals, progress, and challenges
As the research on artificial intelligence booms, there is broad interest in brain‐inspired
computing using novel neuromorphic devices. The potential of various emerging materials …
computing using novel neuromorphic devices. The potential of various emerging materials …
A fully integrated reprogrammable memristor–CMOS system for efficient multiply–accumulate operations
Memristors and memristor crossbar arrays have been widely studied for neuromorphic and
other in-memory computing applications. To achieve optimal system performance, however …
other in-memory computing applications. To achieve optimal system performance, however …
Emerging memristive artificial synapses and neurons for energy‐efficient neuromorphic computing
Memristors have recently attracted significant interest due to their applicability as promising
building blocks of neuromorphic computing and electronic systems. The dynamic …
building blocks of neuromorphic computing and electronic systems. The dynamic …
Efficient and self-adaptive in-situ learning in multilayer memristor neural networks
Memristors with tunable resistance states are emerging building blocks of artificial neural
networks. However, in situ learning on a large-scale multiple-layer memristor network has …
networks. However, in situ learning on a large-scale multiple-layer memristor network has …
The future of electronics based on memristive systems
A memristor is a resistive device with an inherent memory. The theoretical concept of a
memristor was connected to physically measured devices in 2008 and since then there has …
memristor was connected to physically measured devices in 2008 and since then there has …
Analogue signal and image processing with large memristor crossbars
Memristor crossbars offer reconfigurable non-volatile resistance states and could remove
the speed and energy efficiency bottleneck in vector-matrix multiplication, a core computing …
the speed and energy efficiency bottleneck in vector-matrix multiplication, a core computing …
Biological plausibility and stochasticity in scalable VO2 active memristor neurons
W Yi, KK Tsang, SK Lam, X Bai, JA Crowell… - Nature …, 2018 - nature.com
Neuromorphic networks of artificial neurons and synapses can solve computationally hard
problems with energy efficiencies unattainable for von Neumann architectures. For image …
problems with energy efficiencies unattainable for von Neumann architectures. For image …
[HTML][HTML] Brain-inspired computing with memristors: Challenges in devices, circuits, and systems
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 …
computing with memristors. We review the mechanisms of various memristive devices that …