Threshold-type memristor-based crossbar array design and its application in handwritten digit recognition  

作　　者：LI Qingjian LIANG Yan LU Zhenzhou WANG Guangyi 

机构地区：[1]School of Electronic and Information,Hangzhou Dianzi University,Hangzhou 310018,China

出　　处：《Journal of Systems Engineering and Electronics》2023年第2期324-334,共11页系统工程与电子技术（英文版）

基　　金：supported by the National Natural Science Foundation of China(61801154,61771176);the Zhejiang Provincial Natural Science Foundation of China(LY20F010008).

摘　　要：Neuromorphic computing simulates the operation of biological brain function for information processing and can potentially solve the bottleneck of the Von Neumann architecture.Inspired by the real characteristics of physical memristive devices,we propose a threshold-type nonlinear voltage-controlled memristor mathematical model which is used to design a novel memristor-based crossbar array.The presented crossbar array can simulate the synaptic weight in real number field rather than only positive number field.Theoretical analysis and simulation results of a 2×2 image inversion operation validate the feasibility of the proposed crossbar array and the necessary training and inference functions.Finally,the presented crossbar array is used to construct the neural network and then applied in the handwritten digit recognition.The Mixed National Institute of Standards and Technology(MNIST)database is adopted to train this neural network and it achieves a satisfactory accuracy.

关 键 词：MEMRISTOR threshold characteristic MODELLING electrical synapse crossbar array 

分 类 号：TN60[电子电信—电路与系统] TP391.41[自动化与计算机技术—计算机应用技术]