Application of least-squares support vector machine (LS-SVM) to determination of deep level defect centers parameters in semi-insulating GaAs

Stanisław Jankowski; Maciej Knioła; Roman Kozłowski

doi:10.1117/12.714859

12 October 2006 Application of least-squares support vector machine (LS-SVM) to determination of deep level defect centers parameters in semi-insulating GaAs

Stanisław Jankowski, Maciej Knioła, Roman Kozłowski

Author Affiliations +

Proceedings Volume 6347, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2006; 634731 (2006) https://doi.org/10.1117/12.714859
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2006, 2006, Wilga, Poland

Abstract

The purpose of this paper is to present the Least Squares Support Vector Machine (LS-SVM) applied to investigation of deep level defects in semi-insulating gallium arsenide (SI GaAs). LS-SVM was used for spectral surface approximation, computed as a result of Photo Induced Transient Spectroscopy (HRPITS). Deep defects level parameters were extracted based on the spectral surface approximation and Arrhenius equation. Diverse LS-SVM modification was implemented to achieve good quality of estimation.

Citation Download Citation

Stanisław Jankowski, Maciej Knioła, and Roman Kozłowski "Application of least-squares support vector machine (LS-SVM) to determination of deep level defect centers parameters in semi-insulating GaAs", Proc. SPIE 6347, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2006, 634731 (12 October 2006); https://doi.org/10.1117/12.714859

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