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Low Complexity Convolutional Neural Networks for Equalization in Optical Fiber Transmission

arXiv 2210.05454 ↗First posted 11 Oct 2022eess.SP cs.AIcited by 0

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Abstract (arXiv)

A convolutional neural network is proposed to mitigate fiber transmission effects, achieving a five-fold reduction in trainable parameters compared to alternative equalizers, and 3.5 dB improvement in MSE compared to DBP with comparable complexity.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 2 of its 5 references that are in the map. First posted on arXiv 11 Oct 2022.

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References · 2

  1. 2020Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensationcited by 5
  2. 2020Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensationcited by 1

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