神经形态工程学
记忆电阻器
异质结
铁电性
材料科学
神经科学
计算机科学
光电子学
人工智能
电子工程
心理学
人工神经网络
工程类
电介质
作者
Ang Li,Qinxuan Li,Caihong Jia,Weifeng Zhang
标识
DOI:10.1016/j.physb.2023.414777
摘要
Recently, the ferroelectric memristors have attracted much attention for neuromorphic computing and artificial intelligence because of fast reversal speed, excellent fatigue, nondestructive readout. In this paper, the basic functions of biological synapses including paired-pulse facilitation/depression (PPF/PPD), spike-rate/amplitude-dependent plasticity (SRDP/SADP) have been successfully simulated in BaTiO3/Nb:SrTiO3 epitaxial heterojunction. Furthermore, normal and abnormal Bienenstock-Cooper-Munro (BCM) learning rules with sliding frequency threshold have been found from SRDP under positive and negative bias, respectively. This provides support for encoding and deep learning in the application of neuromorphic computing.
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