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Bio

Pedro is a Research Engineer at the Aston Institute of Photonic Technologies (AIPT) in Birmingham, UK. His research focuses on Machine Learning solutions to improve the channel capacity in high-speed optical fiber communications, in particular, new neural network model development, hardware implementation of the neural network, and Data mining in optical signals. Prior to joining AIPT, he was with the Capex Engineer and Commissioning Manager at Royal Vopak-Brazil.

Neural network in high-speed optical fiber communications

Data Science and Machine Learning

  • Session Language |English
I will review the neural network techniques for signal recovery in optical transmission systems, where the neural network equalizers have to deal with considerable nonlinearity and with bi-directional memory effects. Moreover, the problems are characterized by the presence of essential noise. I will concentrate on the specific requirements that we have to impose on the proprieties of efficient neural network equalizers in optical transmission, in particular, the ultra-high accuracy (99.999%), which makes the application of some existing techniques from image recognition and computer vision rather impractical, and the requirement for the reduced complexity of the neural architectures. We will overview the problems that arise when applying neural networks in such nonstationary nonlinear signal processing tasks (high overfitting tendencies and the risk of overestimation), and address the peculiarities of pruning and quantization techniques that arise in optical signal processing.

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