神经形态工程学
MNIST数据库
晶体管
栅氧化层
材料科学
光电子学
电荷(物理)
计算机科学
逻辑门
物理
电气工程
电压
工程类
人工神经网络
算法
人工智能
量子力学
作者
Myung‐Su Kim,Jin‐Ki Kim,Gyeong‐Jun Yun,Ji‐Man Yu,Joon‐Kyu Han,Jung-Woo Lee,Seokho Seo,Shinhyun Choi,Yang‐Kyu Choi
标识
DOI:10.1109/led.2022.3194556
摘要
An overturned charge injection synaptic transistor (OCIST) is experimentally demonstrated for neuromorphic hardware computing. The structure of the OCIST is similar to that of a conventional floating gate memory except for the directionality of charge injection. The charge valve layer (CVL) of the OCIST is analogous to a blocking oxide of a floating gate memory device. The OCIST employs the CVL to control charge flow to the floating gate, while the floating gate memory utilizes a tunneling oxide as a gate oxide for this. Because the CVL and the gate oxide are decoupled in the OCIST, the CVL is independently engineerable without any sacrifice of the gate oxide quality and scalability. Moreover, the selection spectrum for the CVL material is wide. Linearity and symmetry of synaptic potentiation and depression were improved. In addition, a classification accuracy of 92.4% for handwritten digits in the MNIST dataset was achieved.
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