Reduced Complexity Nonlinearity Compensation via Principal Component Analysis and Deep Neural Networks

Yuliang Gao, Ziad A. El-Sahn, Ahmed Awadalla, Demin Yao, Han Sun, Pierre Mertz, Kuang-Tsan Wu. Reduced Complexity Nonlinearity Compensation via Principal Component Analysis and Deep Neural Networks. In Optical Fiber Communications Conference and Exhibition, OFC 2019, San Diego, CA, USA, March 3-7, 2019. pages 1-3, IEEE, 2019. [doi]

@inproceedings{GaoEAYSMW19,
  title = {Reduced Complexity Nonlinearity Compensation via Principal Component Analysis and Deep Neural Networks},
  author = {Yuliang Gao and Ziad A. El-Sahn and Ahmed Awadalla and Demin Yao and Han Sun and Pierre Mertz and Kuang-Tsan Wu},
  year = {2019},
  url = {http://ieeexplore.ieee.org/document/8696296},
  researchr = {https://researchr.org/publication/GaoEAYSMW19},
  cites = {0},
  citedby = {0},
  pages = {1-3},
  booktitle = {Optical Fiber Communications Conference and Exhibition, OFC 2019, San Diego, CA, USA, March 3-7, 2019},
  publisher = {IEEE},
  isbn = {978-1-943580-53-8},
}