Dynamic Response Prediction of Bi-State Emission of Quantum Dot Lasers Based on Extreme Learning Machine

Abstract

Dual-state emission is an phenomenon which takes place in Quantum Dot Lasers at different temperature and operating conditions. In this study, we investigate that issue from a nonlinear regression model based on Extreme Learning Machine, which revealed to be able to predict the spectrally resolved transient response of InAs/InGaAs quantum dot laser with error performance as low as 0.54%.