Controllable SiOx Nanorod Memristive Neuron for Probabilistic Bayesian Inference
Modern artificial neural network technology using a deterministic computing framework is
faced with a critical challenge in dealing with massive data that are largely unstructured and …
faced with a critical challenge in dealing with massive data that are largely unstructured and …
Gradient-based neuromorphic learning on dynamical RRAM arrays
We present MEMprop, the adoption of gradient-based learning to train fully memristive
spiking neural networks (MSNNs). Our approach harnesses intrinsic device dynamics to …
spiking neural networks (MSNNs). Our approach harnesses intrinsic device dynamics to …
Halide perovskite memristor with ultra-high-speed and robust flexibility for artificial neuron applications
Threshold switching (TS) memristor-based artificial neurons have been regarded as one of
the promising solutions for constructing circuits of spiking neural networks (SNNs) due to …
the promising solutions for constructing circuits of spiking neural networks (SNNs) due to …
Low-voltage solution-processed artificial optoelectronic hybrid-integrated neuron based on 2D MXene for multi-task spiking neural network
R Yu, X Zhang, C Gao, E Li, Y Yan, Y Hu, H Chen… - Nano Energy, 2022 - Elsevier
Incorporating optoelectronic integrated capability into artificial neurons can offer critical
benefits of tunable device properties, diverse functions, and efficient computing capacity for …
benefits of tunable device properties, diverse functions, and efficient computing capacity for …
Adaptive Neural Activation and Neuromorphic Processing via Drain‐Injection Threshold‐Switching Float Gate Transistor Memory
H Wang, Y Lu, S Liu, J Yu, M Hu, S Li… - Advanced …, 2023 - Wiley Online Library
Hetero‐modulated neural activation is vital for adaptive information processing and learning
that occurs in brain. To implement brain‐inspired adaptive processing, previously various …
that occurs in brain. To implement brain‐inspired adaptive processing, previously various …
Inkjet-printed h-BN memristors for hardware security
Inkjet printing electronics is a growing market that reached 7.8 billion USD in 2020 and that
is expected to grow to∼ 23 billion USD by 2026, driven by applications like displays …
is expected to grow to∼ 23 billion USD by 2026, driven by applications like displays …
Hardware Implementation of Network Connectivity Relationships Using 2D hBN‐Based Artificial Neuron and Synaptic Devices
Brain‐inspired neuromorphic computing has been developed as a potential candidate for
solving the von Neumann bottleneck of traditional computing systems. 2D materials‐based …
solving the von Neumann bottleneck of traditional computing systems. 2D materials‐based …
Neuromorphic Artificial Vision Systems Based on Reconfigurable Ion‐Modulated Memtransistors
Conventional vision systems suffer from lots of data handling between memory and
processing units. Inspired by how humans recognize noisy images and the flexible …
processing units. Inspired by how humans recognize noisy images and the flexible …
Convolutional Echo‐State Network with Random Memristors for Spatiotemporal Signal Classification
S Wang, H Chen, W Zhang, Y Li… - Advanced Intelligent …, 2022 - Wiley Online Library
The unprecedented development of Internet of Things results in the explosion of
spatiotemporal signals generated by smart edge devices, leading to a surge of interest in …
spatiotemporal signals generated by smart edge devices, leading to a surge of interest in …
A spiking stochastic neuron based on stacked InGaZnO memristors
Spiking encoded stochastic neural network is believed to be energy efficient and biologically
plausible and an increasing effort has been made recently to translate its great cognitive …
plausible and an increasing effort has been made recently to translate its great cognitive …