Artificial Astrocyte Memristor with Recoverable Linearity for Neuromorphic Computing

被引:10
|
作者
Cheng, Caidie [1 ,2 ]
Wang, Yanghao [2 ]
Xu, Liying [2 ]
Liu, Keqin [2 ]
Dang, Bingjie [2 ]
Lu, Yingming [2 ]
Yan, Xiaoqin [1 ]
Huang, Ru [2 ,3 ,4 ]
Yang, Yuchao [2 ,3 ,4 ]
机构
[1] Univ Sci & Technol Beijing, Sch Mat Sci & Engn, State Key Lab Adv Met & Mat, Beijing 100083, Peoples R China
[2] Peking Univ, Sch Integrated Circuits, Key Lab Microelect Devices & Circuits MOE, Beijing 100871, Peoples R China
[3] Peking Univ, Inst Artificial Intelligence, Ctr Brain Inspired Chips, Beijing 100871, Peoples R China
[4] Chinese Inst Brain Res CIBR, Ctr Brain Inspired Intelligence, Beijing 102206, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
artificial astrocyte; image recognition; memristor; neuromorphic computing; nonlinearity; TAOX;
D O I
10.1002/aelm.202100669
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Neuromorphic systems provide a potential solution for overcoming von Neumann bottleneck and realizing computing with low energy consumption and latency. However, the neuromorphic devices utilized to construct the neuromorphic systems always focus on artificial synapses and neurons, and neglected the important role of astrocyte cells. Here, an astrocyte memristor is demonstrated with encapsulated yttria-stabilized zirconia (YSZ) to emulate the function of astrocyte cells in biology. Due to the high oxygen vacancy concentration and resultant high ionic conductivity of YSZ, significantly lower forming and set voltages are achieved in the artificial astrocyte, along with high endurance (>10(11)). More importantly, the nonlinearity in current-voltage characteristics that usually emerge as the testing cycle increases can be depressed in the astrocyte memristor, and the nonlinearity can also be reversed by applying a refresh operation, which implements the role of biological astrocyte in maintaining the normal activity of neurons. The recovery of linearity can dramatically improve the accuracy of Modified National Institute of Standards and Technology dataset classification from 62.98% to 94.75% when the inputs are encoded in voltage amplitudes. The astrocyte memristor in this work with improved performance and linearity recovery characteristics can well emulate the function of astrocyte cells in biology and have great potential for neuromorphic computing.
引用
收藏
页数:7
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