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【摘 要】
：
准分子激光器的放电过程是一个复杂的非线性过程,从而导致基于放电动力学建立的激光器放电能量模型的精度很难达到仿真研究和控制算法设计的需求.通过深度学习的方法,利用门控循环网络辨识准分子激光器放电能量模型.首先基于准分子激光器出光能量特性,选定所建立的门控循环网络的输入.然后根据门控循环神经网络的输入特性和输出特性建立适用于准分子激光器能量模型辨识的神经网络,并介绍了门控循环神经网络训练方法.最后利用实际采集的激光器的能量数据对门控循环神经网络进行训练.实验结果证明,本文所设计的门控循环神经网络收敛,辨识出来
【机 构】
：
中国科学院微电子研究所,北京100029;中国科学院大学,北京100049;北京科益虹源光电技术有限公司技术中心,北京100176;中国科学院微电子研究所,北京100029;北京科益虹源光电技术有限公
【出 处】
：
中国激光
【发表日期】
：
2021年9期
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