Optical Technique, Volume. 51, Issue 4, 392(2025)

OAM mode recognition system of vortex beams based on deep learning and FPGA

HANG Chen, LV Hong*, WANG Kunpeng, LIU Yike, WU Tongqiao, SHAO Ruikang, and HUANG Dingjin
Author Affiliations
  • College of Photoelectric Engineering, Xi 'an University of Technology, Xi 'an 710021, China
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    References(9)

    [4] [4] Ming Z, Xindi T, Weixian W, et al.A novel deep-learning model compression based on filter-stripe group pruning and its IoT application[J]. Sensors,2022,22(15):5623—5623.

    [6] [6] Odetola T A, Groves K M, Mohammed Y, et al. 2L-3W: 2-Level 3-Way hardware-software co-verification for the mapping of convolutional neural network (CNN) onto FPGA boards[J].SN Computer Science,2021,3(1):60.

    [7] [7] Lohani S, Knutson E M, O’Donnell M, et al. On the use of deep neural networks in optical communications[J]. Applied Optics,2018,57(15):4180—4190.

    [8] [8] Qingsong Z, Shiqi H, Yong W, et al. Mode detection of misaligned orbital angular momentum beams based on convolutional neural network[J]. Applied Optics,2018,57(35):10152—10158.

    [9] [9] Wang P, Zhang X, Fan D, et al. Convolutional neural network-assisted optical orbital angular momentum recognition and communication[J]. IEEE Access,2019,7:162025—162035.

    [10] [10] Xizheng K, Meng C. Recognition of orbital angular momentum vortex beam based on convolutional neural network[J]. Microwave and Optical Technology Letters,2021,63(7):1960—1964.

    [12] [12] Wang Z, Lai X, Huang H, et al. Recognizing the orbital angular momentum(OAM) of vortex beams from speckle patterns[J]. Science China(Physics,Mechanics & Astronomy),2022,65(04):59—65.

    [13] [13] Zhang Z, Yin X, Cui X, et al.Performance analysis of modulating retro-reflector link based on orbital angular momentum coding in underwater channels[J]. Optics Communications,2022,510:127903.

    [15] [15] M Z M K, A M R, M M,et al. L-band InAs/InP quantum dash laser spatial OAM light modes classification under smoke environment: an image processing enhanced deep learning approach [J]. Optics and Laser Technology,2024,168:109933.

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    HANG Chen, LV Hong, WANG Kunpeng, LIU Yike, WU Tongqiao, SHAO Ruikang, HUANG Dingjin. OAM mode recognition system of vortex beams based on deep learning and FPGA[J]. Optical Technique, 2025, 51(4): 392

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    Paper Information

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    Received: Mar. 13, 2025

    Accepted: Aug. 12, 2025

    Published Online: Aug. 12, 2025

    The Author Email: LV Hong (lvhong@xatu.edu.cn)

    DOI:

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