Scalable Reservoir Computing Connected via Tapped Delay Lines and Its Application to Nonlinear Equalization in Optical Transmission Systems
We propose a scalable reservoir computing (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$R C$</tex>) configuration that connects small <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$R C$</tex> modules in parallel using tapped delay lines. Our investigation demonstrates improved delay characteristics for nonlinear equalization in optical transmission systems.
Authors
- Takumi Yamamoto (ORCID: https://orcid.org/0000-0002-9223-5987)
- Shuichi Shimomura (ORCID: https://orcid.org/0000-0002-6483-2469)
- Moriya Nakamura
- Kai Ikuta (ORCID: https://orcid.org/0000-0002-5978-057X)
- Tsuyoshi Yamada (ORCID: https://orcid.org/0000-0002-3434-224X)
- Yuta Ito
- Shunya Uchide
Institutions
- Meiji University (JP)
Publication Details
- Published
- 2025-06-29
- DOI
- https://doi.org/10.23919/oecc/psc62146.2025.11109652
- Primary Topic
- Neural Networks and Reservoir Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Japan Society for the Promotion of Science London