12 October 2006 Approximation of HRPITS results for SI GaAs by large scale support vector machine algorithms
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Proceedings Volume 6347, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2006; 634730 (2006) https://doi.org/10.1117/12.714857
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2006, 2006, Wilga, Poland
Abstract
For the first time large-scale support vector machine algorithms are used to extraction defect parameters in semi-insulating (SI) GaAs from high resolution photoinduced transient spectroscopy experiment. By smart decomposition of the data set the SVNTorch algorithm enabled to obtain good approximation of analyzed correlation surface by a parsimonious model (with small number of support vector). The extracted parameters of deep level defect centers from SVM approximation are of good quality as compared to the reference data.
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Stanisław Jankowski, Stanisław Jankowski, Konrad Wojdan, Konrad Wojdan, Zbigniew Szymański, Zbigniew Szymański, Roman Kozłowski, Roman Kozłowski, } "Approximation of HRPITS results for SI GaAs by large scale support vector machine algorithms", Proc. SPIE 6347, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2006, 634730 (12 October 2006); doi: 10.1117/12.714857; https://doi.org/10.1117/12.714857
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