Optical Extreme Learning Machines with Atomic Vapors
Abstract
:1. Introduction
2. Propagation of an Optical Beam in an Atomic Media under Near-Resonant Conditions
3. Building an Optical Extreme Learning Machine
4. Results
4.1. Regression of Nonlinear Functions
4.2. Classification of the Spiral Dataset
5. Discussion and Concluding Remarks
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
ELM | Extreme Learning Machine |
OELM | Optical Extreme Learning Machine |
NSE | Nonlinear Schrödinger equation |
ROI | Region of Interest |
RMSE | Root Mean Squared Error |
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Silva, N.A.; Rocha, V.; Ferreira, T.D. Optical Extreme Learning Machines with Atomic Vapors. Atoms 2024, 12, 10. https://doi.org/10.3390/atoms12020010
Silva NA, Rocha V, Ferreira TD. Optical Extreme Learning Machines with Atomic Vapors. Atoms. 2024; 12(2):10. https://doi.org/10.3390/atoms12020010
Chicago/Turabian StyleSilva, Nuno A., Vicente Rocha, and Tiago D. Ferreira. 2024. "Optical Extreme Learning Machines with Atomic Vapors" Atoms 12, no. 2: 10. https://doi.org/10.3390/atoms12020010
APA StyleSilva, N. A., Rocha, V., & Ferreira, T. D. (2024). Optical Extreme Learning Machines with Atomic Vapors. Atoms, 12(2), 10. https://doi.org/10.3390/atoms12020010