铁电性
冯·诺依曼建筑
隧道枢纽
材料科学
光电子学
油藏计算
纳米技术
计算机科学
量子隧道
人工智能
人工神经网络
操作系统
循环神经网络
电介质
作者
Jihyung Kim,Dahye Kim,Kyung Kyu Min,Matthias Kraatz,Taeyoung Han,Sungjun Kim
标识
DOI:10.1002/aisy.202370036
摘要
Ferroelectric Tunnel Junction Devices In article number 2300080, Jihyung Kim, Dahye Kim, Sungjun Kim, and colleagues demonstrate synaptic functions with a CMOS compatible HfAlOx-based ferroelectric tunnel junction (FTJ) device. Neuroinspired engineering based on an emerging memory is promising to overcome the limitations of von Neumann computing and conventional memories. The FTJ device is also used as a physical reservoir depending on its own properties in reservoir computing. This computing architecture is for processing sequential and temporal inputs based on the biological nervous system.
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