Activation functions of artificial-neural-network-based nonlinear equalizers for optical nonlinearity compensation
نویسندگان
چکیده
We investigated the performance of artificial neural network (ANN)-based nonlinear equalizers for optical nonlinearity compensation by comparing activation functions, including a sigmoid function, ReLU, and Leaky ReLU. compared learning speeds performances evaluating resulting error vector magnitudes compensated signals. The was using simulated 100-km fiber transmission 10-GSymbol/s 16QAM When number hidden-layer units in ANN small, function showed better speed than ReLU This point is important because has to be reduced order improve computational complexity ANN-based equalizer.
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ژورنال
عنوان ژورنال: IEICE communications express
سال: 2021
ISSN: ['2187-0136']
DOI: https://doi.org/10.1587/comex.2021etl0024