Question

跪求英语达人帮忙翻译一下~谢绝借助在线翻译~

经验模态分解方法可以有效提取非线性非稳定信号的瞬时特征。本文主要基于EMD阈值方法和小波分解方法对噪声信号进行去噪，并通过实验结果对比分析，验证了它们各自的优缺点。EMD阈值方法对信号的高频部分效果较好，可以很好地保留信号的高频部分。体现出EMD阈值方法去噪的优势。

Answer 1

Empirical mode decomposition method can effectively extract nonlinear unstable signal feature of instantaneous. This paper based on the EMD method and wavelet threshold value decomposition methods for noise signal de-noising, and through comparison and analysis, the experimental results proved the advantages and disadvantages of each. EMD method of threshold of high frequency part of signal effect is good, can be very good to retain the high frequency part of signal. Reflect EMD threshold denoising method.

~0~

Answer 2

EMD method can extract the instantaneous non-linear non-stable signal characteristics. This threshold is based on EMD method and wavelet denoising the signal to noise, and comparative analysis of the experiment to verify their advantages and disadvantages. EMD threshold method of high-frequency signal is better, you can very well keep the high frequency part. EMD threshold method reflects the advantage of denoising

Answer 3

试着翻译了下, 看看行不行
The empirical mode decomposition method can extract transient features of the non-linear and non-steady signal effectively. This article mainly presents de noise noise signal which based on EMD threshold method and the wavelet transform method, and verifies their respective merits and faults by means of the contrast and analysis of the experimental result. EMD threshold method has an obvious effect of the high-frequency part of the signal, holds the high-frequency part of the signal perfectly which presenting the advantage of EMD threshold method de noise.
兄弟,我可是自己翻译的啊, 不行你就不用采纳了