论文标题
模拟具有神经网络的光纤中的自相似抛物线脉冲
Modelling self-similar parabolic pulses in optical fibres with a neural network
论文作者
论文摘要
我们使用机器学习[OPT。 Laser Technol。，131（2020）106439]在脉搏传播的情况下，在存在增益/损失的情况下，特别关注自相似抛物线脉冲的产生。我们使用监督的前馈神经网络范式来解决与脉冲塑造有关的直接和反向问题，绕开了管理传播模型的直接数值解决方案的需求。
We expand our previous analysis of nonlinear pulse shaping in optical fibres using machine learning [Opt. Laser Technol., 131 (2020) 106439] to the case of pulse propagation in the presence of gain/loss, with a special focus on the generation of self-similar parabolic pulses. We use a supervised feedforward neural network paradigm to solve the direct and inverse problems relating to the pulse shaping, bypassing the need for direct numerical solution of the governing propagation model.
