High Power Laser and Particle Beams, Volume. 36, Issue 7, 071002(2024)
Research progress in deep learning for wavefront reconstruction and wavefront prediction
[1] Jiang Wenhan. Overview of adaptive optics development[J]. Opto-Electronic Engineering, 45, 170489(2018).
[10] [10] Swanson R, Lamb M, Creia C, et al. Wavefront reconstruction prediction with convolutional neural wks[C]Proceedings of SPIE 10703, Adaptive Optics Systems VI. 2018: 107031F.
[12] Hu Shuwen, Hu Lejia, Gong Wei, et al. Deep learning based wavefront sensor for complex wavefront detection in adaptive optical microscopes[J]. Frontiers of Information Technology & Electronic Engineering, 22, 1277-1288(2021).
[32] [32] McGuire P C, Sler D G, LloydHart M, et al. Adaptive optics: neural wk wavefront sensing, reconstruction, prediction[C]Proceedings of the 194th W. E. Heraeus Seminar. 1999: 97138.
[33] [33] Gallant P J, Aitken G J M. Geic algithm design of complexitycontrolled timeseries predicts[C]2003 IEEE XIII Wkshop on Neural wks f Signal Processing. 2003: 769778.
[38] Wang Ning, Zhu Licheng, Ma Shuai, et al. Deep learning-based prediction algorithm on atmospheric turbulence-induced wavefront for adaptive optics[J]. IEEE Photonics Journal, 14, 1-10(2022).
Get Citation
Copy Citation Text
Congpan Qiu, Guodong Liu, Dayong Zhang, Liusen Hu. Research progress in deep learning for wavefront reconstruction and wavefront prediction[J]. High Power Laser and Particle Beams, 2024, 36(7): 071002
Category:
Received: Dec. 5, 2023
Accepted: Jan. 31, 2024
Published Online: Jun. 21, 2024
The Author Email: Liu Guodong (guodliu@126.com)