就随机并行梯度下降(SPGD)最优化算法在光束净化系统中的应用展开研究。
This paper researches the application of the stochastic parallel gradient descent (SPGD) optimization algorithm on the beam cleanup system.
基于随机并行梯度下降（SPGD）算法，32单元变形镜，CCD成像器件等建立了无波前传感自适应光学系统实验平台。
Based on stochastic parallel gradient descent (SPGD) control algorithm, an adaptive optics test-bed without a wave-front sensor was built with a 32-element deformable mirror and a CCD.
随机并行梯度下降(SPGD)算法可以对系统性能指标直接优化来校正畸变波前。
The stochastic parallel gradient descent (SPGD) algorithm can optimize the system performance indexes directly to correct wavefront aberration.
随机并行梯度下降(SPGD)算法可以对系统性能指标直接优化来校正畸变波前。
The stochastic parallel gradient descent (SPGD) algorithm can optimize the system performance indexes directly to correct wavefront aberration.
应用推荐