Highly Linear and Symmetric Analog Neuromorphic Synapse Based on Metal Oxide Semiconductor Transistors with Self‐Assembled Monolayer for High‐Precision Neural Network Computation

Highly Linear and Symmetric Analog Neuromorphic Synapse Based on Metal Oxide Semiconductor Transistors with Self‐Assembled Monolayer for High‐Precision Neural Network Computation

Abstract This work presents an analog neuromorphic synapse device consisting of two oxide semiconductor transistors for high‐precision neural networks. One of the two transistors controls the synaptic weight by charging or discharging the storage node, which leads to a conductance change in the othe...

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Bibliographic Details
Main Authors: Seongmin Park, Suwon Seong, Gilsu Jeon, Wonjae Ji, Kyungmi Noh, Seyoung Kim, Yoonyoung Chung
Format: Article
Language:English
Published: Wiley-VCH 2023-03-01
Series:Advanced Electronic Materials
Subjects:
artificial intelligence
computing‐in‐memory
indium gallium zinc oxide transistor
neuromorphic device
self‐assembled monolayer
Online Access:https://doi.org/10.1002/aelm.202200554

Internet

https://doi.org/10.1002/aelm.202200554

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