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)

Cited 0|Views10
No score
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 ...
More
Translated text
Key words
Training,Supercontinuum generation,Inverse problems,Neural networks,Signal processing,Predictive models,Laser excitation
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined