The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
A programmable diffractive deep neural network based on a digital-coding metasurface array
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“Since the matrix operations in (2) occur automatically during the wave propagation through free space, SIMs can execute complex signal processing and computing tasks without requiring any digital storage, transmission, or preprocessing of information [24].”
From Emerging Technologies in Intelligent Metasurfaces: Shaping the Future of Wireless Communications (2026) · cites this paper as [24]
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“Furthermore, Liu et al. [24] developed a reconfigurable SIM using programmable metasurfaces that can dynamically adjust its EM behavior in real time. Specifically, each metaatom (neuron) is connected to two amplifier chips, providing a dynamic modulation range of 35 dB. A five-layer SIM prototype was fabricated to demonstrate its capability for image recognition and multi-beam focusing [24].”
From Emerging Technologies in Intelligent Metasurfaces: Shaping the Future of Wireless Communications (2026) · cites this paper as [24]
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“The electronically programmable metaatoms within a SIM function similarly to artificial neurons in an ANN, with their complex-valued transmission coefficients serving as trainable network parameters [24].”
From Emerging Technologies in Intelligent Metasurfaces: Shaping the Future of Wireless Communications (2026) · cites this paper as [24]
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“Essentially, the architecture of a SIM forms an EM neural network (EMNN), which is conceptually similar to an ANN [23], [24].”
From Emerging Technologies in Intelligent Metasurfaces: Shaping the Future of Wireless Communications (2026) · cites this paper as [24]
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Cites
LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126
Human-level control through deep reinforcement learning
Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., Graves, A., Riedmiller, M., Fidjeland, A. K., Ostrovski, G., et al. (2015) · Nature · doi:10.1038/nature14236 · Cited by 30,357
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Schmidhuber, J. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.003 · Cited by 18,570
Robust Face Recognition via Sparse Representation
Wright, J. N., Yang, A., Ganesh, A., Sastry, S., & Ma, Y. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.79 · Cited by 9,398
Coding Metamaterials, Digital Metamaterials and Programmable Metamaterials
Cui, T. J., Qi, M. Q., Wan, X., Zhao, J., & Cheng, Q. (2014) · Light: Science & Applications · doi:10.1038/lsa.2014.99 · Cited by 3,801
Self-citationIEEE Transactions on Pattern Analysis and Machine Intelligence
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Deep learning with coherent nanophotonic circuits
Shen, Y., Harris, N. C., Skirlo, S., Prabhu, M., Baehr-Jones, T., Hochberg, M., Sun, X., Zhao, S., Larochelle, H., Englund, D., et al. (2017) · Nature Photonics · doi:10.1038/nphoton.2017.93 · Cited by 3,340
Recent Trends in Deep Learning Based Natural Language Processing [Review Article]
Young, T., Hazarika, D., Poria, S., & Cambria, E. (2018) · IEEE Computational Intelligence Magazine · doi:10.1109/mci.2018.2840738 · Cited by 2,921
All-optical machine learning using diffractive deep neural networks
Lin, X., Rivenson, Y., Yardimci, N. T., Veli, M., Luo, Y., Jarrahi, M., & Ozcan, A. (2018) · Science · doi:10.1126/science.aat8084 · Cited by 2,568
The practical implementation of artificial intelligence technologies in medicine
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Research works printed but not linked: 2
- Cui, T. J., Liu, S., Bai, G. D. & Ma, Q. Direct transmission of digital message via programmable coding metasurface. Research 2019, 2584509 (2019).
- Kingma, D. P. & Ba, J. L. Adam: a method for stochastic optimization. in 3rd International Conference on Learning Representations (2015).
Cited by
Sorted by citations
Stacked Intelligent Metasurfaces for Efficient Holographic MIMO Communications in 6G
An, J., Xu, C., Ng, D. W. K., Alexandropoulos, G. C., Huang, C., Yuen, C., & Hanzo, L. (2023) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2023.3288261 · Cited by 358
Intelligent metasurfaces: control, communication and computing
Li, L., Zhao, H., Li, L., Li, L., & Cui, T. J. (2022) · eLight · doi:10.1186/s43593-022-00013-3 · Cited by 359
Self-citationHigh-throughput terahertz imaging: progress and challenges
Li, X., Li, J., Li, Y., Özcan, A., & Jarrahi, M. (2023) · Light Science & Applications · doi:10.1038/s41377-023-01278-0 · Cited by 313
Optical neural networks: progress and challenges
Fu, T., Zhang, J., Sun, R. C., Huang, Y., Xu, W. X., Yang, S., Zhu, Z., & Chen, H. (2024) · Light Science & Applications · doi:10.1038/s41377-024-01590-3 · Cited by 339
Photonic multiplexing techniques for neuromorphic computing
Bai, Y., Xu, X., Tan, M., Sun, Y., Li, Y., Wu, J., Morandotti, R., Mitchell, A., Xu, K., & Moss, D. (2023) · Nanophotonics · doi:10.1515/nanoph-2022-0485 · Cited by 316
Metadata
- Authors
- Liu, C., Ma, Q., Luo, Z. J., Hong, Q. R., Xiao, Q., Zhang, H. C., Miao, L., Yu, W. M., Cheng, Q., Li, L., & Cui, T. J.
- Affiliations
- State Key Laboratory of Millimeter Waves (CN)
- Peking University (CN)
- Corresponding author
- Cui, Tie Jun
- ORCID
- Venue
- Nature Electronics
- Published
- 2022-02-21
- Volume
- 5
- Issue
- 2
- Pages
- 113-122
- ISSN
- 2520-1131 (ISSN-L)
- OpenAlex
- W4212835306
- Cited by
- 633
- References
- 45
- Citations by year
- 2026: 111 · 2025: 178 · 2024: 171 · 2023: 115 · 2022: 55
- FWCI
- 29.92
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Nature Electronics (publishedVersion)
- Research Square (acceptedVersion, cc-by)
- Funders
- National Key Research and Development Program of China (2017YFA0700201, 2017YFA0700203, 2017YFA0700202)
- Topics
- Physical Sciences › Materials Science › Electronic, Optical and Magnetic Materials › Metamaterials and Metasurfaces Applications
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Antenna and Metasurface Technologies
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Reservoir Computing
- Keywords
- diffractive deep neural networks, metasurface arrays, digital encoding, on-chip learning, reinforcement learning, discrete optimization, image classification, all-optical computing
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