@inproceedings{f176582734074e75aefd54ccfc0adb54,
title = "Pruned Volterra Nonlinear Equalization using Sparse Bayesian Learning and Kalman Filtering",
abstract = "A sparsified Volterra algorithm based on sparse Bayesian learning and Kalman filtering is proposed and experimentally demonstrated in a 20G-baud PAM4 IM/DD system, reducing the average retained kernel number by 90.43\%.",
keywords = "IM/DD optical communication system, Kalman filtering, Sparse Bayesian learning, Volterra",
author = "Hualei Shi and Feng Tian and Chuanji Yan and Yutian Li and Qi Zhang and Ran Gao and Qinghua Tian and Fu Wang and Zhipei Li",
note = "Publisher Copyright: {\textcopyright} 2026 IEEE.; 24th International Conference on Optical Communications and Networks, ICOCN 2026 ; Conference date: 20-07-2026 Through 23-07-2026",
year = "2026",
doi = "10.1109/ICOCN70692.2026.11656170",
language = "English",
series = "2026 24th International Conference on Optical Communications and Networks, ICOCN 2026",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2026 24th International Conference on Optical Communications and Networks, ICOCN 2026",
address = "United States",
}