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Adaptive merit function in SPGD algorithm for beam combining
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作者 杨国庆 刘立生 +2 位作者 姜振华 王挺峰 郭劲 《Optoelectronics Letters》 EI 2016年第5期398-400,共3页
The beam pointing is the most crucial issue for beam combining to achieve high energy laser output. In order to meet the turbulence situation, a beam pointing method that cooperates with the stochastic parallel gradie... The beam pointing is the most crucial issue for beam combining to achieve high energy laser output. In order to meet the turbulence situation, a beam pointing method that cooperates with the stochastic parallel gradient descent(SPGD) algorithm is proposed. The power-in-the-bucket(PIB) is chosen as the merit function, and its radius changes gradually during the correction process. The linear radius and the exponential radius are simulated. The results show that the exponential radius has great promise for beam pointing. 展开更多
关键词 pointing turbulence exponential correction merit radius stochastic chosen descent disturbance
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