A Ti/AIOX/TaOX/Pt Analog Synapse for Memristive Neural Network

被引：42

作者：

Sun, Yi ^{[1
]}

Xu, Hui ^{[1
]}

Wang, Chao ^{[2
]}

Song, Bing ^{[1
]}

Liu, Haijun ^{[1
]}

Liu, Qi ^{[3
]}

Liu, Sen ^{[1
]}

Li, Qingjiang ^{[1
]}

机构：

[1] Natl Univ Def Technol, Coll Elect Sci, Changsha 410073, Hunan, Peoples R China

[2] Chinese Acad Sci, Suzhou Inst Nanotech & Nanobion, Key Lab Nano Devices & Applicat, Suzhou 215123, Peoples R China

[3] Chinese Acad Sci, Inst Microelect, Key Lab Microelect Device & Integrated Technol, Beijing 100029, Peoples R China

来源：

IEEE ELECTRON DEVICE LETTERS | 2018年 / 39卷 / 09期

基金：

中国国家自然科学基金;

关键词：

Neuromorphic computing; memristor; analog synapse; long-term retention; TERM PLASTICITY; CLASSIFICATION;

D O I：

10.1109/LED.2018.2860053

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Electronic synapse with precise analog weight tuning ability and long-term retention is the vital device foundation of memristor-based neuromorphic computing systems. In this letter, we propose a Ti/AlOX/TaOX/Pt memristor as an analog synapse for memristive neural network applications. The device shows high uniformity, excellent analog switching behaviors (up to 200 resistance states under triangle pulses) and excellent long-term retention of each state (up to 30 000 s). Furthermore, the precise modulation of the device resistance state (with 1.7% tolerance) can also be achieved by a finer writing program within 50 cycles.

引用

页码：1298 / 1301

页数：4

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