论文信息 - Simulation of wavefront sensorless correction based on Stochastic Parallel Gradient Descent algorithm

Simulation of wavefront sensorless correction based on Stochastic Parallel Gradient Descent algorithm

Stochastic Parallel Gradient Descent(SPGD) algorithm can optimize the system exhibition firsthand without using of wavefront sensor, it predigests the adaptive optic system. Based on SPGD algotithm, a model with 32 element demormable mirror was simulated, the capability of correct toward static aberration and convergence of SPGD algorithm are analysed, the relationship of gain coefficient, stochastic perturbation amplitude are discussed, an adaptive adjustment of gain coefficient is proposed, and it can improve convergence rate effectively.

Gang Wang

[1] Mikhail A Vorontsov,et al. Decoupled stochastic parallel gradient descent optimization for adaptive optics: integrated approach for wave-front sensor information fusion. , 2002, Journal of the Optical Society of America. A, Optics, image science, and vision.

[2] Gert Cauwenberghs,et al. Adaptive wavefront correction: a hybrid VLSI/optical system implementing parallel stochastic gradient descent , 1999, Remote Sensing.

[3] M A Vorontsov,et al. Adaptive phase-distortion correction based on parallel gradient-descent optimization. , 1997, Optics letters.

[4] Mikhail A. Vorontsov,et al. Stochastic parallel-gradient-descent technique for high-resolution wave-front phase-distortion correction , 1998 .

[5] Gert Cauwenberghs,et al. A Fast Stochastic Error-Descent Algorithm for Supervised Learning and Optimization , 1992, NIPS.