The transient temperature rise in the active region in AlGaN/GaN high electron mobility transistors （HEMTs） is measured using an electrical method. The original data are smoothed and denoised by a nonparametric fitt...The transient temperature rise in the active region in AlGaN/GaN high electron mobility transistors （HEMTs） is measured using an electrical method. The original data are smoothed and denoised by a nonparametric fitting algorithm, called locally weighted scatterplot smoothing （LOWESS）. The thermal time-constant spectrum is extracted to analyze the physical structure of the heat-conduction path in A1GaN/GaN HEMTs. The thermal time- constant spectra extracted using the LOWESS algorithm are richer and the RC network obtained is greater compared with those with the traditional denoising method （multi-exponential fitting）. Thus, the analysis of the heat-flow path is more precise. The results show that the LOWESS nonparametric fitting algorithm can remove noise from measured data better than other methods and can retain the subtle variation tendency of the original discrete data. The thermal time-constant spectra extracted using this method can describe the subtle temperature variations in the A1GaN/GaN HEMT active region. This will help researchers to precisely analyze the layer composition of the heat-flow path.展开更多
文摘The transient temperature rise in the active region in AlGaN/GaN high electron mobility transistors （HEMTs） is measured using an electrical method. The original data are smoothed and denoised by a nonparametric fitting algorithm, called locally weighted scatterplot smoothing （LOWESS）. The thermal time-constant spectrum is extracted to analyze the physical structure of the heat-conduction path in A1GaN/GaN HEMTs. The thermal time- constant spectra extracted using the LOWESS algorithm are richer and the RC network obtained is greater compared with those with the traditional denoising method （multi-exponential fitting）. Thus, the analysis of the heat-flow path is more precise. The results show that the LOWESS nonparametric fitting algorithm can remove noise from measured data better than other methods and can retain the subtle variation tendency of the original discrete data. The thermal time-constant spectra extracted using this method can describe the subtle temperature variations in the A1GaN/GaN HEMT active region. This will help researchers to precisely analyze the layer composition of the heat-flow path.
