Neural Networks based Equalization of Experimental Transmission using the Nonlinear Fourier Transformation

We use cross-correlations between continuous and discrete parts of the nonlinear Fourier spectrum to train an equalizer based on neural networks. In a dual-polarization transmission experiment reach improvements of more than 2000 km and up to beyond 5000 km were achieved.