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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
Deep learning in neural networks: an overview
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
(2004) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2004.1307293 · Cited by 3,708
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
He, J., Baxter, S. L., Xu, J., Xu, J., Zhou, X., & Zhang, K. (2019) · Nature Medicine · doi:10.1038/s41591-018-0307-0 · Cited by 2,246
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).
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Teng, X., Tang, W., Li, X., & Jin, S. (2025) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2025.3632886 · Cited by 1
Ma, H., Jiang, P., Qiao, X., Chen, Z., & Nie, X. (2025) · Applied Optics · doi:10.1364/ao.579833 · Cited by 1
Luan, H., Xing, Y., Bai, Y., Dong, Y., & Gu, M. (2026) · Light Advanced Manufacturing · doi:10.37188/lam.2026.031 · Cited by 1
CNNs in the Air via Reconfigurable Intelligent Surfaces
Hua, M., Wu, H., & Gündüz, D. (2026) · IEEE Wireless Communications Letters · doi:10.1109/lwc.2026.3672551 · Cited by 1
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Li, Z., An, J., & Yuen, C. (2025) · Globecom · doi:10.1109/globecom59602.2025.11431689 · Cited by 1
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Nerini, M., Liu, X., & Clerckx, B. (2026) · IEEE Transactions on Microwave Theory and Techniques · doi:10.1109/tmtt.2026.3721382 · Cited by 1
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Li, J. C., An, J., Liu, H., Gan, L., Leung, V. C. M., Bennis, M., & Debbah, M. A. (2026) · IEEE Wireless Communications Letters · doi:10.1109/lwc.2026.3688611 · Cited by 1
Ibrahim, M., Mezghani, A., & Hossain, E. (2026) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2026.3696550 · Cited by 1
Tunable resonant metasurfaces enabled by atomically thin semiconductors
Ustinov, A. B., Barreda, A. I., Choi, D., Bucher, T., Soavi, G., Pertsch, T., & Staude, I. (2026) · Light Science & Applications · doi:10.1038/s41377-026-02311-8 · Cited by 1
Qiu, T., Li, W., Wang, J., Wang, J., An, Q., Liu, B., Hou, Y., Jiang, J., Tang, W., Cheng, Z., et al. (2023) · Journal of Physics D Applied Physics · doi:10.1088/1361-6463/acbf63 · Cited by 1
Diffractive Deep Neural Network for Microwave Imaging Based on a Multi-Layer Transmitarray Antenna
Liu, D., Shan, T., Li, M., Yang, F., & Xu, S. (2023) · doi:10.23919/aces-china60289.2023.10249573 · Cited by 1
Location-Based Beamforming Design for Multi-Layer RIS Assisted MIMO
Zhang, H., Wang, J., & Li, Y. (2024) · IEEE Vehicular Technology Conference · doi:10.1109/vtc2024-spring62846.2024.10683268 · Cited by 1
Self-citation
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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