记忆电阻器
神经形态工程学
材料科学
记忆
重置(财务)
突触
电压
光电子学
纳米技术
过程(计算)
计算机科学
电子工程
人工智能
人工神经网络
神经科学
电气工程
工程类
生物
数学教育
经济
操作系统
金融经济学
数学
作者
Lei Liu,Wen Xiong,Yanxin Liu,Kaige Chen,Zhong Xu,Yi Zhou,Han Jia,Cong Ye,Xin Chen,Zhitang Song,Min Zhu
标识
DOI:10.1002/aelm.201901012
摘要
Abstract HfO 2 ‐based memristors that remembers the history of the current that has passed through them have attracted great interest for use as artificial synapses in neuromorphic systems. However, the low resistance contrast exhibited by HfO 2 ‐based memristors seriously decreases their recognition accuracy. By inserting a 2 nm BiFeO 3 layer a large memory window of 10 4 and remarkable pulse endurance of 10 8 cycles are achieved. Multilevel storage capability is also demonstrated by controlling the stop voltages in the RESET process. The conductance–modulation characteristics of a BiFeO 3 /HfO 2 memristor can be used to mimic the learning behaviors of biological synapses, and spiking timing dependent plasticity is mimicked, which is viewed as an important learning rule of biological synapses. Moreover pattern learning and memorization ability like the human brain are achieved by a 3 × 3 memristive device array.
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