Low-Complexity Multi-Task Learning Aided Neural Networks for Equalization in Short-Reach Optical Interconnects-Reference-Cited by-同舟云学术

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Low-Complexity Multi-Task Learning Aided Neural Networks for Equalization in Short-Reach Optical Interconnects

Published:2022-01 Issue:1 Volume:40 Page:45-54
ISSN:0733-8724
Container-title:Journal of Lightwave Technology
language:
Short-container-title:J. Lightwave Technol.

Author:

Xu Zhaopeng^ORCID,Dong Shuangyu,Manton Jonathan H.^ORCID,Shieh William^ORCID

Funder

Australian Research Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atomic and Molecular Physics, and Optics

Link

http://xplorestaging.ieee.org/ielx7/50/9664591/09560044.pdf?arnumber=9560044

Cited by 24 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Photonics-aided D-band 64-QAM MMW transmission utilizing modified multi-symbol output neural network equalization;Optical Fiber Technology;2024-10

2. High-Speed Dispersion-Unmanaged DML-Based IM-DD Optics at C-band With Advanced Nonlinear Equalization and Noise Whitening;Journal of Lightwave Technology;2024-08-15

3. Low-Complexity Samples Versus Symbols-Based Neural Network Receiver for Channel Equalization;Journal of Lightwave Technology;2024-08-01

4. Advanced Neural Network-Based Equalization in Intensity-Modulated Direct-Detection Optical Systems: Current Status and Future Trends;Photonics;2024-07-28

5. Key Enablers for Hardware-Efficient Neural Network Receiver in Short-Reach Optical Links;2024 22nd International Conference on Optical Communications and Networks (ICOCN);2024-07-26

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