Please log in to access this page.
Please log in to access this page.
Please log in to access this page.
Please log in to access this page.
Code for Digital Twin of Atmospheric Turbulence Phase Screens Based On Deep Neural Networks
贾鹏
This is a complied version of digital twin of atmospheric turbulence phase screens based on deep neural networks. It can only generate phase screens with 128*128 pixels. If you need some phase screen with specified properties, feel free to contact the corresponding author: Peng Jia from Taiyuan University of Techonology through his email: robinmartin20@gmail.com or robinmartin@126.com.
Files
IFATS_code.zip
285.53 MB
Paper Information
Paper Title:
Digital Twin of Atmospheric Turbulence Phase Screens Based On Deep Neural Networks
Publication:
Optics Express
Identifiers
CSTR:
11379.11.101110
DOI:
10.12149/101110
VO Identifier:
ivo://China-VO/paperdata/OE/jiapeng2022/101110
Publication Date:
2022-05-24
Citation Guidelines
贾鹏 et al. 2022. Code for Digital Twin of Atmospheric Turbulence Phase Screens Based On Deep Neural Networks. Version 1.0. https://doi.org/10.12149/101110
@misc{10.12149/101110,
doi = {10.12149/101110},
url = {https://doi.org/10.12149/101110},
author = {贾鹏},
title = {Code for Digital Twin of Atmospheric Turbulence Phase Screens Based On Deep Neural Networks},
version = {1.0},
publisher = {Nataional Astronomical Data Center of China},
year= {2022}
}
doi = {10.12149/101110},
url = {https://doi.org/10.12149/101110},
author = {贾鹏},
title = {Code for Digital Twin of Atmospheric Turbulence Phase Screens Based On Deep Neural Networks},
version = {1.0},
publisher = {Nataional Astronomical Data Center of China},
year= {2022}
}
Versions
Main
This DOI represents all versions, and will always resolve to the latest one.
2022-05-23