ma huimin, zhang pengfei, zhang jinghui, et al. Stochastic parallel gradient descent algorithm for adaptive optics system[J]. High Power Laser and Particle Beams, 2010, 22.
Citation:
ma huimin, zhang pengfei, zhang jinghui, et al. Stochastic parallel gradient descent algorithm for adaptive optics system[J]. High Power Laser and Particle Beams, 2010, 22.
ma huimin, zhang pengfei, zhang jinghui, et al. Stochastic parallel gradient descent algorithm for adaptive optics system[J]. High Power Laser and Particle Beams, 2010, 22.
Citation:
ma huimin, zhang pengfei, zhang jinghui, et al. Stochastic parallel gradient descent algorithm for adaptive optics system[J]. High Power Laser and Particle Beams, 2010, 22.
Key Laboratory of Atmospheric Composition and Optical Radiation,Anhui Institute of Optics and Fine Mechanics,Chinese Academy of Sciences,Hefei 230031,China
The stochastic parallel gradient descent(SPGD) algorithm can optimize the system performance indexes directly to correct wavefront aberration. A 61-element adaptive optics system model based on SPGD algorithm was simulated. For different initial static aberrations, the algorithm’s correction capabilities were analyzed. The selections of algorithm gain coefficient and perturbation amplitude were compared in the conditions of adopting different performance indexes, and so was the correction effects. Simulation results demonstrate that the algorithm’s convergence rate depends on gain coefficient and perturbation amplitude to a great extent. For relatively severe aberrations with perturbation amplitude ranging from 0.50 to 0.85, the correction effects of using mean radius as the system perfo
DownLoad: