Dongting Hu, Wen Shen, Wenchao Ma, Xinyu Liu, Zhouping Su, Huaxin Zhu, Xiumei Zhang, Lizhi Que, Zhuowei Zhu, Yixin Zhang, Guoqing Chen, Lifa Hu. Fast Convergence Stochastic Parallel Gradient Descent Algorithm[J]. Laser & Optoelectronics Progress, 2019, 56(12): 122201
- Laser & Optoelectronics Progress
- Vol. 56, Issue 12, 122201 (2019)
Fig. 1. Block diagram of adaptive optics system without wavefront detection
Fig. 2. Actuator distribution of 69-actuator deformable mirror
Fig. 3. Flow chart of SPGD algorithm
Fig. 4. Convergence for single random test and averaging after multiple tests under 800 iterations
Fig. 5. Effects of perturbation amplitude δ and gain coefficient γ on residual wavefront and its optimal fitting curve
Fig. 6. Optimal solution for wavefronts with different initial distortions. (a) Wavefronts with three initial distortion magnitudes; (b) distribution of optimal curve for wavefronts with different initial distortions
Fig. 7. Convergence under different parameter combinations for wavefronts with different initial distortions. (a) 0.3312 rad;(b)0.8448 rad;(c)1.3180 rad
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Table 1. Convergence under different parameter combinations for wavefront with initial distortion RMS of 0.3312 rad
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Table 2. Convergence of different parameter combinations for wavefront with initial distortion RMS of 0.8448 rad
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Table 3. Convergence of different parameter combinations for wavefront with initial distortion RMS of 1.3180 rad
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