Tyrosine-mediated analog resistive switching for artificial neural networks-Reference-Cited by-同舟云学术

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Tyrosine-mediated analog resistive switching for artificial neural networks

Published:2022-08-17 Issue:1 Volume:16 Page:858-864
ISSN:1998-0124
Container-title:Nano Research
language:en
Short-container-title:Nano Res.

Author:

Song Min-Kyu,Namgung Seok Daniel,Lee Hojung,Yoon Jeong Hyun,Song Young-Woong,Cho Kang Hee,Lee Yoon-Sik,Lee Jong-Seok,Nam Ki Tae,Kwon Jang-Yeon

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,General Materials Science,Condensed Matter Physics,Atomic and Molecular Physics, and Optics

Link

https://link.springer.com/content/pdf/10.1007/s12274-022-4760-1.pdf

Reference52 articles.

1. LeCun, Y.; Bengio, Y.; Hinton, G. Deep learning. Nature 2015, 521, 436–444.

2. Furber, S. Large-scale neuromorphic computing systems. J. Neural Eng. 2016, 13, 051001.

3. Yu, S. M. Neuro-Inspired Computing Using Resistive Synaptic Devices; Springer: Cham, 2017.

4. Burr, G. W.; Narayanan, P.; Shelby, R. M.; Ambrogio, S.; Tsai, H.; Lewis, S. L.; Hosokawa, K. Neuromorphic devices and architectures for next-generation cognitive computing. In 2017 IEEE International Symposium on Circuits and Systems (ISCAS), Baltimore, USA, 2017, pp 1–4.

5. Woo, J.; Kim, J. H.; Im, J. P.; Moon, S. E. Recent advancements in emerging neuromorphic device technologies. Adv. Intell. Syst. 2020, 2, 2000111.

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