mlsanityData to 14 Oct 2026

Energy-efficient Spiking Neural Network Equalization for IM/DD Systems with Optimized Neural Encoding

arXiv 2312.12909 ↗First posted 20 Dec 2023eess.SP cs.LG cs.NEcited by 1

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Abstract (arXiv)

We propose an energy-efficient equalizer for IM/DD systems based on spiking neural networks. We optimize a neural spike encoding that boosts the equalizer's performance while decreasing energy consumption.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 5 of its 8 references that are in the map. First posted on arXiv 20 Dec 2023.

Builds on

5 of 8 references.

References · 5

  1. 2019Surrogate Gradient Learning in Spiking Neural Networkscited by 626
  2. 2020SPOQ ℓp-Over-ℓq Regularization for Sparse Signal Recovery applied to Mass Spectrometrycited by 3
  3. 2022Spiking Neural Network Equalization for IM/DD Optical Communicationcited by 3
  4. 2022Spiking Neural Network Decision Feedback Equalizationcited by 3
  5. 2023Spiking Neural Network Decision Feedback Equalization for IM/DD Systemscited by 1

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Cited by year

Citing papers per year: 2024: 1.

1 paper.

  1. 2024Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communicationscited by 0