• Acta Optica Sinica
  • Vol. 34, Issue s1, 101006 (2014)
Luo Cheng*, Su Rongtao, Wang Xiaolin, and Zhou Pu
Author Affiliations
  • [in Chinese]
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    DOI: 10.3788/aos201434.s101006 Cite this Article Set citation alerts
    Luo Cheng, Su Rongtao, Wang Xiaolin, Zhou Pu. Adaptive Stochastic Parallel Gradient Descent Algorithm and Its Application in Coherent Beam Combining[J]. Acta Optica Sinica, 2014, 34(s1): 101006 Copy Citation Text show less

    Abstract

    The fundamental theory for coherent beam combing (CBC) via using stochastic parallel gradient descent (SPGD) algorithm is introduced and an adaptive SPGD algorithm is proposed. The convergence rate is increased by adaptively controlling the perturbations and stages of the SPGD algorithm. The results show that for CBC of laser arrays with 25 channels, 49 channels and 100 channels by using adaptive SPGD algorithm, the convergence rates are increased by 36.6%, 59.8% and 80.2%, respectively. This method has an advantage for CBC of laser arrays with large number of lasers.
    Luo Cheng, Su Rongtao, Wang Xiaolin, Zhou Pu. Adaptive Stochastic Parallel Gradient Descent Algorithm and Its Application in Coherent Beam Combining[J]. Acta Optica Sinica, 2014, 34(s1): 101006
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