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- W604685728 abstract "In the Tibetan Plateau, due to lack of raw experimental data sets and proper data analysis method, investigations on atmosphere laser communication channel (ALCC), especially under rainy condition, are rarely concerned by researchers. Neural network group and optimal weight initialization technology (OWIT) are adopted in the analysis process. Firstly, construct neural network group according to different season’s conditions. Secondly, utilize existed raw data sets of ALCC under rainy condition to choose matching initial weight sets with OWIT. Thirdly, train neural network group until expected requirement is met. Finally, load rain data sets from the Tibetan Plateau (Lhasa for example) on trained neural network group to achieve the ultimate channel quality of ALCC. Actual results show that spring rain has the best quality of ALCC, followed by winter rain, summer rain and autumn rain." @default.
- W604685728 created "2016-06-24" @default.
- W604685728 creator A5066142640 @default.
- W604685728 date "2015-05-29" @default.
- W604685728 modified "2023-09-24" @default.
- W604685728 title "Feature Analysis on Atmosphere Laser Communication Channel Under Rainy Condition in the Tibetan Plateau" @default.
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- W604685728 doi "https://doi.org/10.2174/1874129001509010147" @default.
- W604685728 hasPublicationYear "2015" @default.
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