113 citations · 191 across the 5 of their papers we have counts for
5 papers
Deep Learning Waveform Channel Modeling for Wideband Optical Fiber Transmission: Model Comparisons, Challenges and Potential Solutions
Minghui Shi, Hang Yang, Zekun Niu +6
Fast and accurate waveform simulation is critical for understanding fiber channel characteristics, developing digital signal processing (DSP) technologies, optimizing optical netwo…
Fast predicting the complex nonlinear dynamics of mode-locked fiber laser by a recurrent neural network with prior information feeding
Guoqing Pu, Runmin Liu, Hang Yang +4
As an imperative method of investigating the internal mechanism of femtosecond lasers, traditional femtosecond laser modeling relies on the split-step Fourier method (SSFM) to iter…
Low-complexity full-field ultrafast nonlinear dynamics prediction by a convolutional feature separation modeling method
Hang Yang, Haochen Zhao, Zekun Niu +4
The modeling and prediction of the ultrafast nonlinear dynamics in the optical fiber are essential for the studies of laser design, experimental optimization, and other fundamental…
Fast and accurate waveform modeling of long-haul multi-channel optical fiber transmission using a hybrid model-data driven scheme
Hang Yang, Zekun Niu, Haochen Zhao +3
The modeling of optical wave propagation in optical fiber is a task of fast and accurate solving the nonlinear Schrödinger equation (NLSE), and can enable the optical system design…
Fast and Accurate Optical Fiber Channel Modeling Using Generative Adversarial Network
Hang Yang, Zekun Niu, Shilin Xiao +4
In this work, a new data-driven fiber channel modeling method, generative adversarial network (GAN) is investigated to learn the distribution of fiber channel transfer function. Ou…