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

机译:在线支持向量机识别Si(A4)的缺陷结构

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摘要

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.
机译:本文提出了在线支持向量机在光谱表面近似中的应用。对于中子辐照硅样品,通过光电流衰减测量得到的实验数据是时间和温度的函数。这种方法能够提取深层中心缺陷参数:活化能和指数前因子。

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