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    Journals >Acta Physica Sinica >Volume 69 >Issue 1 >Page 014209-1 > Article
    • Acta Physica Sinica
    • Vol. 69, Issue 1, 014209-1 (2020)
    Extracting atmospheric turbulence phase using deep convolutional neural network
    Qi-Wei Xu1、2, Pei-Pei Wang1、2, Zhen-Jia Zeng2, Ze-Bin Huang2, Xin-Xing Zhou3, Jun-Min Liu1、*, Ying Li2, Shu-Qing Chen2, and Dian-Yuan Fan2
    Author Affiliations
  • 1College of New Materials and New Energies, Shenzhen Technology University, Shenzhen 518118, China
  • 2Engineering Technology Research Center for 2D Material Information Function Devices and Systems of Guangdong Province, International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology, Shenzhen University, Shenzhen 518060, China
  • 3Synergetic Innovation Center for Quantum Effects and Applications, School of Physics and Electronics, Hunan Normal University, Changsha 410081, China
    • show less
    DOI: 10.7498/aps.69.20190982 Cite this Article
    Qi-Wei Xu, Pei-Pei Wang, Zhen-Jia Zeng, Ze-Bin Huang, Xin-Xing Zhou, Jun-Min Liu, Ying Li, Shu-Qing Chen, Dian-Yuan Fan. Extracting atmospheric turbulence phase using deep convolutional neural network[J]. Acta Physica Sinica, 2020, 69(1): 014209-1 Copy Citation Text show less
    References

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    Qi-Wei Xu, Pei-Pei Wang, Zhen-Jia Zeng, Ze-Bin Huang, Xin-Xing Zhou, Jun-Min Liu, Ying Li, Shu-Qing Chen, Dian-Yuan Fan. Extracting atmospheric turbulence phase using deep convolutional neural network[J]. Acta Physica Sinica, 2020, 69(1): 014209-1
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