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An approach for automatic construction of the wavelet-domain de-noising procedure for THz pulsed spectroscopy signal processing

机译:一种自动构建小波域去噪程序的方法,用于THz脉冲光谱信号处理

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De-noising of terahertz pulsed spectroscopy (TPS) signals is an essential problem, since a noise in the TPS data samples makes correct reconstruction of sample spectral dielectric properties and internal structure challenging. It is especially important for the spectral regions where detector sensitivity is typically low. A lot of effective techniques for 1D and 2D signal de-noising based on the signal processing in wavelet-domain have been developed in recent times. The present work demonstrates the ability to perform effective de-noising of pulsed spectroscopy signals using the algorithm of the Fast Wavelet Transform (FWT). The results of optimal wavelet basis selection and the results of adaptive wavelet-domain filter selection are reported. The performance of the wavelet-domain de-noising algorithm implementation is also discussed. A technique for automatic construction of the wavelet-domain de-noising procedure is offered.
机译:太赫兹脉冲光谱(TPS)信号的去噪是一个重要的问题,因为TPS数据样本中的噪声使得样本光谱介电性能的正确重建和内部结构具有挑战性。对于探测器灵敏度通常低的光谱区域尤为重要。近期已经开发了许多基于小波域中的信号处理的1D和2D信号去噪的有效技术。本工作表明使用快速小波变换(FWT)的算法执行脉冲光谱信号的有效脱光信号的能力。报道了最佳小波选择的结果和自适应小波域滤波器选择的结果。还讨论了小波域取消通知算法实现的性能。提供了一种自动构建小波域去噪程序的技术。

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