Self-rectifying-based memristors for neuromorphic computing.

Huang, Wen; Hang, Pengjie; Yang, Deren; Yu, Xuegong; Li, Xing'ao

Huang, Wen; Hang, Pengjie; Yang, Deren; Yu, Xuegong; Li, Xing'ao.

Afiliación

Huang W; New Energy Technology Engineering Laboratory of Jiangsu Province, School of Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; State Key Laboratory of Silicon Materials, Zhejiang University, Hangzhou 310027, China.
Hang P; State Key Laboratory of Silicon Materials, Zhejiang University, Hangzhou 310027, China.
Yang D; State Key Laboratory of Silicon Materials, Zhejiang University, Hangzhou 310027, China.
Yu X; State Key Laboratory of Silicon Materials, Zhejiang University, Hangzhou 310027, China. Electronic address: yuxuegong@zju.edu.cn.
Li X; New Energy Technology Engineering Laboratory of Jiangsu Province, School of Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; School of Science, Zhejiang University of Science & Technology, Hangzhou 310027, China. Electronic address: lixa@njupt.edu.cn.

Sci Bull (Beijing) ; 67(12): 1213-1216, 2022 06 30.

Article en En | MEDLINE | ID: mdl-36546147

Asunto(s)

Redes Neurales de la Computación; Sinapsis

Palabras clave

Memristors; Neuromorphic computing; Self-rectifying effects; Synaptic devices

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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Sinapsis / Redes Neurales de la Computación Idioma: En Revista: Sci Bull (Beijing) Año: 2022 Tipo del documento: Article

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