Edge learning using a fully integrated neuro-inspired memristor chip

Learning is highly important for edge intelligence devices to adapt to different application scenes and owners. Current technologies for training neural networks require moving massive amounts of data between computing and memory units, which hinders the implementation of learning on edge devices. W...

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Veröffentlicht in:	Science (American Association for the Advancement of Science) Jg. 381; H. 6663; S. 1205
Hauptverfasser:	Zhang, Wenbin, Yao, Peng, Gao, Bin, Liu, Qi, Wu, Dong, Zhang, Qingtian, Li, Yuankun, Qin, Qi, Li, Jiaming, Zhu, Zhenhua, Cai, Yi, Wu, Dabin, Tang, Jianshi, Qian, He, Wang, Yu, Wu, Huaqiang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	15.09.2023
ISSN:	1095-9203, 1095-9203
Online-Zugang:	Weitere Angaben
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