Results 41 to 50 of about 13,642,405 (235)

Organic electronics for neuromorphic computing [PDF]

open access: yes, 2018
Neuromorphic computing could address the inherent limitations of conventional silicon technology in dedicated machine learning applications. Recent work on silicon-based asynchronous spiking neural networks and large crossbar-arrays of two-terminal ...
van de Burgt, Y   +5 more
core   +3 more sources

Review and outlook on synaptic devices and chips for neuromorphic systems

open access: yesGongneng cailiao yu qijian xuebao
As the limitations of traditional von Neumann architecture in handling big data and artificial intelligence applications become increasingly apparent, new computing architectures such as Computing-In-Memory (CIM) and neuromorphic computing have gradually
Sai-ke ZHU, Yi ZHAO
doaj   +1 more source

Recent Progress of Neuromorphic Computing Based on Silicon Photonics: Electronic–Photonic Co-Design, Device, and Architecture

open access: yesPhotonics, 2022
The rapid development of neural networks has led to tremendous applications in image segmentation, speech recognition, and medical image diagnosis, etc. Among various hardware implementations of neural networks, silicon photonics is considered one of the
Bo Xu   +5 more
doaj   +1 more source

Intermediate Resistive State in Wafer‐Scale Vertical MoS2 Memristors Through Lateral Silver Filament Growth for Artificial Synapse Applications

open access: yesAdvanced Functional Materials, EarlyView.
In MOCVD MoS2 memristors, a current compliance‐regulated Ag filament mechanism is revealed. The filament ruptures spontaneously during volatile switching, while subsequent growth proceeds vertically through the MoS2 layers and then laterally along the van der Waals gaps during nonvolatile switching.
Yuan Fa   +19 more
wiley   +1 more source

Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip

open access: yesNature Communications
By mimicking the neurons and synapses of the human brain and employing spiking neural networks on neuromorphic chips, neuromorphic computing offers a promising energy-efficient machine intelligence.
Man Yao   +17 more
doaj   +1 more source

Halide Perovskites for Neuromorphic Computing

open access: yes, 2023
The next generation of neuromorphic computing, which is related to emulating the neural structure and operation of the human brain, will extend into areas that correspond to human cognition, such as interpretation and autonomous adaptation.
Anthopoulos, Thomas D.   +6 more
core   +1 more source

Integration of Low‐Voltage Nanoscale MoS2 Memristors on CMOS Microchips

open access: yesAdvanced Functional Materials, EarlyView.
This article presents the first monolithic integration of nanoscale MoS2‐based memristors into the back‐end‐of‐line of foundry‐fabricated CMOS microchips in a one‐transistor‐one‐resistor (1T1R) architecture. The MoS2‐based 1T1R cells exhibit forming‐free, nonvolatile resistive switching with ultra‐low operating voltages, low cycle‐to‐cycle variability ...
Jimin Lee   +16 more
wiley   +1 more source

Research on neuromorphic vision sensor and its applications

open access: yes物联网学报, 2019
Neuromorphic vision sensor is a biologically inspired artificial neural system that mimics algorithmic behavior of biological vision systems,which has numerous advantages over standard vision sensors,such as high temporal resolution,low latency,low power,
Yongsheng SANG   +4 more
doaj   +2 more sources

Optoelectronic Synaptic Devices Using Molecular Telluride Phase‐Change Inks for Three‐Factor Learning

open access: yesAdvanced Functional Materials, EarlyView.
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner   +14 more
wiley   +1 more source

ReSe2-Based RRAM and Circuit-Level Model for Neuromorphic Computing

open access: yesFrontiers in Nanotechnology, 2021
Resistive random-access memory (RRAM) devices have drawn increasing interest for the simplicity of its structure, low power consumption and applicability to neuromorphic computing.
Yifu Huang   +8 more
doaj   +1 more source

Home - About - Disclaimer - Privacy