Journal Physics D: Applied Physics, volume 51, issue 50, pages 503002

Review of memristor devices in neuromorphic computing: materials sciences and device challenges

Yibo Li 1
Zhenlin Wang 1
Rivu Midya 1
Qiangfei Xia 1
Jyisy Yang 1
1
 
Department of Electrical and Computer Engineering, University of Massachusetts Amherst, Amherst, MA 01003, United States of America
Publication typeJournal Article
Publication date2018-09-24
Q1
Q2
SJR0.681
CiteScore6.8
Impact factor3.1
ISSN00223727, 13616463
Surfaces, Coatings and Films
Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Acoustics and Ultrasonics

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GOST |
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GOST Copy
Li Y. et al. Review of memristor devices in neuromorphic computing: materials sciences and device challenges // Journal Physics D: Applied Physics. 2018. Vol. 51. No. 50. p. 503002.
GOST all authors (up to 50) Copy
Li Y., Wang Z., Midya R., Xia Q., Yang J. Review of memristor devices in neuromorphic computing: materials sciences and device challenges // Journal Physics D: Applied Physics. 2018. Vol. 51. No. 50. p. 503002.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1088/1361-6463/aade3f
UR - https://doi.org/10.1088/1361-6463/aade3f
TI - Review of memristor devices in neuromorphic computing: materials sciences and device challenges
T2 - Journal Physics D: Applied Physics
AU - Li, Yibo
AU - Wang, Zhenlin
AU - Midya, Rivu
AU - Xia, Qiangfei
AU - Yang, Jyisy
PY - 2018
DA - 2018/09/24
PB - IOP Publishing
SP - 503002
IS - 50
VL - 51
SN - 0022-3727
SN - 1361-6463
ER -
BibTex |
Cite this
BibTex (up to 50 authors) Copy
@article{2018_Li,
author = {Yibo Li and Zhenlin Wang and Rivu Midya and Qiangfei Xia and Jyisy Yang},
title = {Review of memristor devices in neuromorphic computing: materials sciences and device challenges},
journal = {Journal Physics D: Applied Physics},
year = {2018},
volume = {51},
publisher = {IOP Publishing},
month = {sep},
url = {https://doi.org/10.1088/1361-6463/aade3f},
number = {50},
pages = {503002},
doi = {10.1088/1361-6463/aade3f}
}
MLA
Cite this
MLA Copy
Li, Yibo, et al. “Review of memristor devices in neuromorphic computing: materials sciences and device challenges.” Journal Physics D: Applied Physics, vol. 51, no. 50, Sep. 2018, p. 503002. https://doi.org/10.1088/1361-6463/aade3f.
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