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Synergy of CNN with Random Forest based hybrid architecture to estimate the quality of Coherent optical communication

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AI-based-Modulation-Classification

Synergy of CNN with Random Forest based hybrid architecture to estimate the quality of Coherent optical communication

In this project, a hybrid approach was used by combining CNN and Random Forest regressor to estimate the Error Vector Magnitude (EVM) parameter accurately. EVM plays a crucial role in monitoring the signal quality to determine the performance of coherent optical communications.

DATASET AVAILABILITY - Yuchuan Fan, Aleksejs Udalcovs, Xiaodan Pang, Carlos Natal�ino, Marija Furdek, Sergei Popov, Oskars Ozolins, November 24, 2020, ”2020 JOCN Constellation Dataset”, IEEE Dataport, doi: https://dx.doi.org/10.21227/1684-a275.

Paper was published in this topic. Reference link: https://ieeexplore.ieee.org/document/10430241

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Synergy of CNN with Random Forest based hybrid architecture to estimate the quality of Coherent optical communication

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