Main > Photonics Research >  Volume 8 >  Issue 6 >  Page 06000940 > Article
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  • Received: Feb. 4, 2020

    Accepted: Mar. 27, 2020

    Posted: Mar. 30, 2020

    Published Online: May. 20, 2020

    The Author Email: Xing Lin (lin-x@tsinghua.edu.cn), Qionghai Dai (qhdai@tsinghua.edu.cn)

    DOI: 10.1364/PRJ.389553

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    Tiankuang Zhou, Lu Fang, Tao Yan, Jiamin Wu, Yipeng Li, Jingtao Fan, Huaqiang Wu, Xing Lin, Qionghai Dai. In situ optical backpropagation training of diffractive optical neural networks[J]. Photonics Research, 2020, 8(6): 06000940

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  • Table 1. Computational Performance of the Proposed Optical Training Architecturea

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    Table 1. Computational Performance of the Proposed Optical Training Architecturea

    In situ Optical Training ApplicationsMNIST ClassificationMatrix-Vector MultiplicationDe-scattering (Fashion-MNIST)
    PerformanceAccuracy: 91.86%Relative error: 1.13%PSNR: 22.00  dB
    Number of layers (N)1048
    Neurons per layer (M×M)150×150200×200200×200
    Total parameters225,000160,000320,000
    Training time per iteration (s)0.080.080.08
    Energy efficiency [MAC/(s·W)]7.86×10115.85×10111.17×1012

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