A physics-based deep learning (DL) method termed Phynet is proposed for modeling the
nonlinear pulse propagation in optical fibers totally independent of the ground truth. The …

In this work, we analyze different types of recurrent neural networks (RNNs) working under
several different parameters to best model the nonlinear optical dynamics of pulse …

摘要近年来随着计算机性能的提高, 机器学习中的神经网络发展迅速, 在诸多领域中得到了成功
的应用. 在超快光学中, 基于神经网络技术的一些应用在过去几年中也受到了越来越多的关注 …

We present a unique approach for learning the pulse evolution in a nonlinear fiber using a
deep convolutional neural network (CNN) by solving the nonlinear Schrodinger equation …

The nonlinear evolution of ultrashort pulses in optical fiber has broad applications, but the
computational burden of convolutional numerical solutions necessitates rapid modeling …

The initial state of a nonlinear optical fiber system plays a vital role in the ultrafast pulse
evolution dynamic. In this work, a data-driven compressed convolutional neural network …

We deploy a supervised machine-learning model based on a neural network to predict the
temporal and spectral reshaping of a simple sinusoidal modulation into a pulse train having …

To accurately predict the complex dynamical processes of supercontinuum generation in
optical fibers, an integrated deep learning model was constructed in this study, fully …

摘要提出一种借助机器学习算法从信号非完整信息提取待测参量的方法, 该方法以只包含信号
部分信息的功率谱幅度数据取代包含脉冲幅度和相位全部信息的数据来完成参量提取 …

With the evolution of 5G wireless communications, the Synchronization Signal Block (SSB)
plays a critical role in the synchronization of devices and accessibility of services. However …