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Proceedings Paper

Application of least-squares support vector machine (LS-SVM) to determination of deep level defect centers parameters in semi-insulating GaAs
Author(s): Stanisław Jankowski; Maciej Knioła; Roman Kozłowski
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Paper 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.

Paper Details

Date Published: 12 October 2006
PDF: 7 pages
Proc. SPIE 6347, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2006, 634731 (12 October 2006); doi: 10.1117/12.714859
Show Author Affiliations
Stanisław Jankowski, Warsaw Univ. of Technology (Poland)
Maciej Knioła, Warsaw Univ. of Technology (Poland)
Roman Kozłowski, Institute of Electronic Materials Technology (Poland)


Published in SPIE Proceedings Vol. 6347:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2006
Ryszard S. Romaniuk, Editor(s)

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