Recognition of defect structure of Si(A4) by on-line support vector machine

Details Recognition of defect structure of Si(A4) by on-line support vector machine Recognition of defect structure of Si(A4) by on-line support vector machine

Jan 2008

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008spie.6937e..68d&link_type=abstract

Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2007. Edited by Romaniuk, Rys

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In this paper the application of on-line support vector machine to spectral surface approximation is presented. The experimental data were obtained by the photocurrent decay measurement as function of time and temperature for a sample of neutron irradiated silicon. This approach enabled to extract the deep level center defect parameters: activation energy and pre-exponential factor.

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