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Journals >Nano-Micro Letters >Volume 16 >Issue 1 >Page 166 > Article

Nano-Micro Letters
Vol. 16, Issue 1, 166 (2024)

A Fully-Integrated Memristor Chip for Edge Learning

Yanhong Zhang, Liang Chu^*, and Wenjun Li^**

Author Affiliations

School of Electronics and Information, Hangzhou Dianzi University, Hangzhou 310018, People’s Republic of China

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DOI: 10.1007/s40820-024-01368-7 Cite this Article

Yanhong Zhang, Liang Chu, Wenjun Li. A Fully-Integrated Memristor Chip for Edge Learning[J]. Nano-Micro Letters, 2024, 16(1): 166 Copy Citation Text

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References

[1] W. Zhang, P. Yao, B. Gao, Q. Liu, D. Wu et al., Edge learning using a fully integrated neuro-inspired memristor chip. Science 381, 1205–1211 (2023).

[2] B. Gao, B. Lin, Y. Pang, F. Xu, Y. Lu et al., Concealable physically unclonable function chip with a memristor array. Sci. Adv. 8, eabn7753 (2022).

[3] X. Li, J. Tang, Q. Zhang, B. Gao, J.J. Yang et al., Power-efficient neural network with artificial dendrites. Nat. Nanotechnol. 15, 776–782 (2020).

[4] M. Rao, H. Tang, J. Wu, W. Song, M. Zhang et al., Thousands of conductance levels in memristors integrated on CMOS. Nature 615, 823–829 (2023).

[5] W. Wan, R. Kubendran, C. Schaefer, S.B. Eryilmaz, W. Zhang et al., A compute-in-memory chip based on resistive random-access memory. Nature 608, 504–512 (2022).

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Yanhong Zhang, Liang Chu, Wenjun Li. A Fully-Integrated Memristor Chip for Edge Learning[J]. Nano-Micro Letters, 2024, 16(1): 166

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