MACHINE LEARNING-BASED METHOD FOR ANALYZING CHARAC
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专利名称：MACHINE LEARNING-BASED METHOD FOR ANALYZING CHARACTERISTICS OF LASER
BEAM PROPAGATION THROUGH
TURBULENT ATMOSPHERE
发明人：CHEN, Chunyi,FENG, Xin,TONG,
Shoufeng,JIANG, Zhengang,YANG, Huamin 申请号：AU2020102396
申请日：20200923
公开号：AU2020102396A4
公开日：
20201105
专利内容由知识产权出版社提供
摘要：#$%^&*AU2020102396A420201105.pdf##### ABSTRACT The disclosure discloses a machine learning-based method for analyzing characteristics of laser beam propagation through a turbulent atmosphere. The method includes: firstly, performing a measuring operation for the normalized variance of received optical signal intensity fluctuations under different external propagation conditions and creating a training sample set for a multi-layer feedforward neural network; secondly, training the multi-layer feedforward neural network by using the created training sample set to approximate a functional relation between the normalized variance of received optical signal intensity fluctuations and external propagation conditions; and finally, obtaining the normalized variance of received optical signal intensity fluctuations under particular external propagation conditions using the multi-layer feedforward neural network. Since dimensionless parameters are used as inputs to the multi-layer feedforward neural network in the method, the multi-layer feedforward neural network built according to
the method can be used to predict the normalized variance of received optical signal intensity fluctuations under those external propagation conditions that are not applied for experimental measuring. DRAWINGS 101 102 End-------------- ---- ---------------- Ed 201 202 End A 17End B urbulent Atmosphere Channel 203 204 FIG.1I
申请人：Changchun University of Science and Technology
代理人：ASPIDES PTY LTD
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