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The Application of Improved Spatial Correlation Wavelet Denoising in Terahertz Time-domain Spectroscopy

机译:改进的空间相关小波去噪在太赫兹时域光谱中的应用

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In this paper, the original spatial correlation wavelet denoising has been improved and applied to analyze the data of Terahertz time-domain spectroscopy (THz-TDS). The improved algorithm has introduced the conception of threshold coefficient and a suitable threshold to end iteration process of algorithm. Then introduce the scale discriminate coefficient and obtain the adaptive coefficient according to that the noise and signal modulus maxima has different changes with the increasing scale. The experiment result shows that the algorithm based on improved spatial correlation denoising can not only reduce the number of iteration to save computation time, but also improve the measuring precision of THz-TDS effectively.
机译:本文对原始的空间相关小波去噪进行了改进,并将其用于分析太赫兹时域光谱(THz-TDS)的数据。改进的算法引入了阈值系数的概念和合适的阈值来结束算法的迭代过程。然后引入标度判别系数,根据噪声和信号模量最大值随标度的增加而变化的差异,引入标度判别系数,得到自适应系数。实验结果表明,基于改进的空间相关降噪的算法不仅可以减少迭代次数,节省计算时间,而且可以有效提高THz-TDS的测量精度。

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