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A novel EMD selecting thresholding method based on multiple iteration for denoising LIDAR signal

机译:一种基于多次迭代的EMD选择阈值去噪LIDAR信号的新方法

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摘要

Empirical mode decomposition (EMD) approach has been believed to be potentially useful for processing the nonlinear and non-stationary LIDAR signals. To shed further light on its performance, we proposed the EMD selecting thresholding method based on multiple iteration, which essentially acts as a development of EMD interval thresholding (EMD-IT), and randomly alters the samples of noisy parts of all the corrupted intrinsic mode functions to generate a better effect of iteration. Simulations on both synthetic signals and LIDAR signals from real world support this method.
机译:经验模态分解(EMD)方法已被认为对处理非线性和非平稳LIDAR信号很有用。为了进一步揭示其性能,我们提出了基于多次迭代的EMD选择阈值方法,该方法本质上是作为EMD间隔阈值(EMD-IT)的发展,并随机更改了所有损坏的固有模式的噪声部分的样本函数以产生更好的迭代效果。来自现实世界的合成信号和LIDAR信号的仿真均支持该方法。

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