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We present a novel approach for Quality of Transmission estimation using hybrid modelling and transfer-learning. Our method reduces the training data requirement by 80.27dB. The approach facilitates a streamlined ML life-cycle for data collection, training and deployment.
|Title of host publication||Asia Communications and Photonics Conference/International Conference on Information Photonics and Optical Communications 2020 (ACP/IPOC)|
|Publisher||Optical Society of America (OSA)|
|Publication status||Published - 26 Oct 2020|
- Erbium doped fiber amplifiers
- Network topology
- Neural networks
- Optical networks
- Optical signal to noise ratio
- Stochastic gradient descent
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