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Nonlinear interference mitigation via deep neural networks

Publication ,  Conference
Hager, C; Pfister, HD
Published in: 2018 Optical Fiber Communications Conference and Exposition, OFC 2018 - Proceedings
June 13, 2018

A neural-network-based approach is presented to efficiently implement digital backpropagation (DBP). For a 32×100 km fiber-optic link, the resulting 'learned' DBP significantly reduces the complexity compared to conventional DBP implementations.

Duke Scholars

Published In

2018 Optical Fiber Communications Conference and Exposition, OFC 2018 - Proceedings

ISBN

9781943580385

Publication Date

June 13, 2018

Start / End Page

1 / 3
 

Citation

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Hager, C., & Pfister, H. D. (2018). Nonlinear interference mitigation via deep neural networks. In 2018 Optical Fiber Communications Conference and Exposition, OFC 2018 - Proceedings (pp. 1–3).
Hager, C., and H. D. Pfister. “Nonlinear interference mitigation via deep neural networks.” In 2018 Optical Fiber Communications Conference and Exposition, OFC 2018 - Proceedings, 1–3, 2018.
Hager C, Pfister HD. Nonlinear interference mitigation via deep neural networks. In: 2018 Optical Fiber Communications Conference and Exposition, OFC 2018 - Proceedings. 2018. p. 1–3.
Hager, C., and H. D. Pfister. “Nonlinear interference mitigation via deep neural networks.” 2018 Optical Fiber Communications Conference and Exposition, OFC 2018 - Proceedings, 2018, pp. 1–3.
Hager C, Pfister HD. Nonlinear interference mitigation via deep neural networks. 2018 Optical Fiber Communications Conference and Exposition, OFC 2018 - Proceedings. 2018. p. 1–3.

Published In

2018 Optical Fiber Communications Conference and Exposition, OFC 2018 - Proceedings

ISBN

9781943580385

Publication Date

June 13, 2018

Start / End Page

1 / 3