A Weighted Loss Function to Predict Control Parameters for Supercontinuum Generation Via Neural Networks
2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP)(2021)
Abstract
Supercontinuum light is generated by a train of laser pulses propagating in an optical fiber. The parameters characterizing these pulses influence the spectrum of the light as it exits the fiber. While spectrum generation is a direct process governed by nonlinear equations that can be reproduced through numerical simulation, determining the parameters of the pulse generating a given spectrum is a ...
MoreTranslated text
Key words
Training,Supercontinuum generation,Inverse problems,Neural networks,Signal processing,Predictive models,Laser excitation
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined