A TaOx-Based Electronic Synapse With High Precision for Neuromorphic Computing

被引:7
|
作者
Liu, Sen [1 ]
Li, Kun [1 ]
Sun, Yi [1 ]
Zhu, Xi [1 ]
Li, Zhiwei [1 ]
Song, Bing [1 ]
Liu, Haijun [1 ]
Li, Qingjiang [1 ]
机构
[1] Natl Univ Def Technol, Coll Elect Sci & Technol, Changsha 410073, Peoples R China
来源
IEEE ACCESS | 2019年 / 7卷
基金
中国国家自然科学基金;
关键词
Memristor; electronic synapse; neuromorphic computing; MNIST classification; MEMORY; DEVICE;
D O I
10.1109/ACCESS.2019.2961166
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Neuromorphic computing is a promising candidate for breaking the von Neumann bottleneck and developing high-efficient computing systems. Here we present a W/TaOx/Pt high-precision electronic synapse with excellent analog properties for neuromorphic computing. The device exhibits the potential of 10-bit weight precision, which is state of the art in conductance levels. Furthermore, the device shows linear weight update behavior in a specific conductance range, linear I-V curves in low voltage regime, long time retention, and precise modulation of weight. These characteristics are very helpful for improving the accuracy of neuromorphic networks. Finally, a 400 x 60 x 10 three-layer perceptron was constructed with W/TaOx/Pt synapses for MNIST classification and similar to 92% accuracy was achieved.
引用
收藏
页码:184700 / 184706
页数:7
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