@inproceedings{545fd8fe075b40308d5559fa60a6e91e,
title = "CNN Nonlinear Equalizer with Reducing the Dimensionality of Feature Maps",
abstract = "In this paper, we propose a method of feature map dimensionality reduction as the input of CNN. We validate the complexity advantages of this scheme in a 120Gb/s PDM 64QAM coherent optical communication system.",
keywords = "Non-linear compensation, dimensionality reduction, perturbation theory",
author = "Shuo Liu and Yongjun Wang and Lu Han and Chao Li and Xingyuan Huang and Qi Zhang and Xiangjun Xin",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 21st International Conference on Optical Communications and Networks, ICOCN 2023 ; Conference date: 31-07-2023 Through 03-08-2023",
year = "2023",
doi = "10.1109/ICOCN59242.2023.10236423",
language = "English",
series = "2023 21st International Conference on Optical Communications and Networks, ICOCN 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 21st International Conference on Optical Communications and Networks, ICOCN 2023",
address = "United States",
}