相干脉冲叠加放大作为深度递归神经网络的设计与运行

Hanzhang Pei, M. Whittlesey, Qiang Du, A. Galvanauskas
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引用次数: 0

摘要

我们展示了相干脉冲叠加系统与深度递归神经网络的等效性,并通过实验证明了对叠加腔和输入脉冲的实时学习,这是高保真相干时间组合所需的~ 102脉冲。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and Operation of Coherent Pulse Stacking Amplification as a Deep Recurrent Neural Network
We show equivalence of coherent pulse stacking system to a deep recurrent neural network, and experimentally demonstrate real-time learning on stacking cavities and input pulses, necessary for high fidelity coherent temporal combining with ∼102 pulses.
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