Learning for Perturbation-Based Fiber Nonlinearity Compensation Article Swipe
Shenghang Luo
,
Sunish Kumar Orappanpara Soman
,
Lutz Lampe
,
Jeebak Mitra
,
Chuandong Li
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2210.03440
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2210.03440
Several machine learning inspired methods for perturbation-based fiber nonlinearity (PBNLC) compensation have been presented in recent literature. We critically revisit acclaimed benefits of those over non-learned methods. Numerical results suggest that learned linear processing of perturbation triplets of PB-NLC is preferable over feedforward neural-network solutions.
Related Topics
Concepts
Perturbation (astronomy)
Nonlinear system
Feed forward
Artificial neural network
Feedforward neural network
Computer science
Compensation (psychology)
Control theory (sociology)
Artificial intelligence
Physics
Control engineering
Engineering
Psychology
Quantum mechanics
Psychoanalysis
Control (management)
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2210.03440
- https://arxiv.org/pdf/2210.03440
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4304192835
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4304192835Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2210.03440Digital Object Identifier
- Title
-
Learning for Perturbation-Based Fiber Nonlinearity CompensationWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
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2022-10-07Full publication date if available
- Authors
-
Shenghang Luo, Sunish Kumar Orappanpara Soman, Lutz Lampe, Jeebak Mitra, Chuandong LiList of authors in order
- Landing page
-
https://arxiv.org/abs/2210.03440Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2210.03440Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2210.03440Direct OA link when available
- Concepts
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Perturbation (astronomy), Nonlinear system, Feed forward, Artificial neural network, Feedforward neural network, Computer science, Compensation (psychology), Control theory (sociology), Artificial intelligence, Physics, Control engineering, Engineering, Psychology, Quantum mechanics, Psychoanalysis, Control (management)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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