Experimental estimation of optical nonlinear memory channel conditional distribution using deep neural networks-Reference-Cited by-同舟云学术

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Experimental estimation of optical nonlinear memory channel conditional distribution using deep neural networks

Published:2017 Issue: Volume: Page:
ISSN:
Container-title:Optical Fiber Communication Conference
language:
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Author:

Rios-Müller Rafael,Estarán José Manuel,Renaudier Jeremie

Publisher

OSA

Reference6 articles.

1. Experimental study of 112 Gb/s short reach transmission employing PAM formats and SiP intensity modulator at 13 μm

2. Transmission of 2 × 56 Gb/s PAM-4 signal over 100 km SSMF using 18 GHz DMLs

3. 140-Gb/s 20-km Transmission of PAM-4 Signal at 1.3 $\mu \text{m}$ for Short Reach Communications

4. Optimal decoding of linear codes for minimizing symbol error rate (Corresp.)

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1. Semi-Supervised Feature-Crosses Neural Network Equalizer in Fiber Optics;2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings (ACP/POEM);2023-11-04

2. DSP optimization technique based on deep learning to account for the effects of fiber nonlinearity;Highlights in Science, Engineering and Technology;2023-06-30

3. Activation functions of artificial-neural-network-based nonlinear equalizers for optical nonlinearity compensation;IEICE Communications Express;2021-08-01

4. Photonic machine learning implementation for signal recovery in optical communications;Scientific Reports;2018-05-31

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