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Design of CMOS-memristor hybrid synapse and its application for noise-tolerant memristive spiking neural network.

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第一作者： Jae Gwang,Lim

第一单位： Center for Semiconductor Technology, Korea Institute of Science and Technology, Seoul, Republic of Korea.;School of Electrical Engineering, Korea University, Seoul, Republic of Korea.

作者： Jae Gwang,Lim ^[1] ; Sang Min,Lee ^[2] ; Sung-Jae,Park ^[2] ; Joon Young,Kwak ^[3] ; Yeonjoo,Jeong ^[4] ; Jaewook,Kim ^[4] ; Suyoun,Lee ^[4] ; Jongkil,Park ^[4] ; Gyu Weon,Hwang ^[4] ; Kyeong-Seok,Lee ^[4] ; Seongsik,Park ^[4] ; Byeong-Kwon,Ju ^[5] ; Hyun Jae,Jang ^[4] ; Jong Keuk,Park ^[4] ; Inho,Kim ^[4]

作者单位： Center for Semiconductor Technology, Korea Institute of Science and Technology, Seoul, Republic of Korea.;School of Electrical Engineering, Korea University, Seoul, Republic of Korea. ^[1] Center for Semiconductor Technology, Korea Institute of Science and Technology, Seoul, Republic of Korea.;Department of Micro/Nano Systems, Korea University, Seoul, Republic of Korea. ^[2] Division of Electronic and Semiconductor Engineering, Ewha Womans University, Seoul, Republic of Korea. ^[3] Center for Semiconductor Technology, Korea Institute of Science and Technology, Seoul, Republic of Korea. ^[4] School of Electrical Engineering, Korea University, Seoul, Republic of Korea.;Department of Micro/Nano Systems, Korea University, Seoul, Republic of Korea. ^[5]

关键词 CMOS memristor hybrid synapse SPICE simulation artificial synapse memristor neuromorphic hardware spiking neural network surrogate gradient learning

DOI 10.3389/fnins.2025.1516971

PMID 40109662

发布时间 2025-03-20

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