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.

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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.

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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.

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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.

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