材料科学与工程学报2017，Vol.35Issue(2)：232-236,5.DOI:10.14136/j.cnki.issn 1673-2812.2017.02.013
基于ZnO忆阻器的神经突触仿生电子器件
Synaptic Devices Based on ZnO Memristors
摘要
Abstract
ZnO memristive devices have been employed to emulate synaptic memory and learning functions.ZnO synaptic devices show a typical excitatory post-synaptic current (EPSC),i.e.exponentially decreasing with time,and pair-pulse facilitation behavior of EPSC.Furthermore,the learning-forgettingrelearning empirical behavior and four types of spike-timing-dependent-plasticity learning rules have been implemented.Ultra-low energy consumption operation has been realized in ZnO synaptic devices showing a minimum energy consumption of 1.6pJ for a single synaptic behavior.The results indicate that ZnO synaptic devices can be potentially used to construct the future artificial neural networks in hardware and ultimately develop cognitive computers operating like human brains and humanoid robots.关键词
忆阻器/神经突触器件/人工神经网络/ZnOKey words
memristors/synaptic devices/artificial neural networks/ZnO分类
通用工业技术引用本文复制引用
潘若冰,诸葛飞,胡丽娟,曹鸿涛,竺立强,李俊,李康,梁凌燕,张洪亮,高俊华..基于ZnO忆阻器的神经突触仿生电子器件[J].材料科学与工程学报,2017,35(2):232-236,5.基金项目
国家自然科学基金资助项目(51272261和61474127) （51272261和61474127）
