RRAM-based synapse devices for neuromorphic systems
Author:
Affiliation:
1. Pohang University of Science and Technology (POSTECH)
2. Korea
Abstract
We demonstrated a proton-based 3-terminal synapse device which shows symmetric conductance change characteristics. Using the optimized device, we successfully confirmed the improved classification accuracy of neural networks for on-chip training.
Funder
National Research Foundation of Korea
Publisher
Royal Society of Chemistry (RSC)
Subject
Physical and Theoretical Chemistry
Link
http://pubs.rsc.org/en/content/articlepdf/2019/FD/C8FD00127H
Reference41 articles.
1. Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices: Design Considerations
2. Improved Synaptic Behavior Under Identical Pulses Using AlOx/HfO2Bilayer RRAM Array for Neuromorphic Systems
3. Improved Synaptic Behavior Under Identical Pulses Using AlOx/HfO2Bilayer RRAM Array for Neuromorphic Systems
4. Effect of conductance linearity and multi-level cell characteristics of TaOx-based synapse device on pattern recognition accuracy of neuromorphic system
5. Improved Synapse Device With MLC and Conductance Linearity Using Quantized Conduction for Neuromorphic Systems
Cited by 160 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Implementation of Artificial Synapse Using IGZO-Based Resistive Switching Device;Materials;2024-01-19
2. Annealing Effects on the Charging–Discharging Mechanism in Trilayer Al2O3/Ge/Al2O3 Memory Structures;ACS Applied Electronic Materials;2024-01-17
3. Engineered Vertically Stacked NSFET Charge-Trapping Synapse for Neuromorphic Applications;ACS Applied Electronic Materials;2023-12-04
4. Impact of TID on the Analog Conductance and Training Accuracy of CBRAM-Based Neural Accelerator;IEEE Transactions on Nuclear Science;2023-12
5. Improved Resistive Switching Characteristics and Synaptic Functions of InZnO/SiO2 Bilayer Device;Materials;2023-11-24
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3