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The research on denoising using wavelet transform

机译：小波变换去噪的研究

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As wavelet transform is widely used in many fields, wavelet theory plays an important role in signal processing, because of it's advantages of getting bigger output SNR and obtaining better smoothness filtering effect. First of all, the paper elaborates the advantages and fundamental concept of wavelet transform and multi-resolution. Then, it expatiates the process of signal denoising using wavelet transform. Four signals, including heavy sine, bumps, doppler and quadchirp, polluted by the noise are selected as sample data and Minimum Mean Square Error is used to go on denoising process. Then, we elaborate advantages and disadvantages of two methods, including hard threshold and soft threshold denoising, according to the comparison of denoised signal, high frequency segments and output signal-to-noise ratio. Finally, we draw the conclusion.
机译：由于小波变换在许多领域得到了广泛的应用，因此小波理论在获得更大的输出信噪比和获得更好的平滑滤波效果方面具有重要的作用。首先，阐述了小波变换和多分辨率的优点和基本概念。然后，阐述了利用小波变换进行信号去噪的过程。选择由噪声污染的四个正弦信号，颠簸信号，多普勒信号和四分频信号作为采样数据，并使用最小均方误差进行降噪处理。然后，根据去噪信号，高频段和输出信噪比的比较，阐述了硬阈值和软阈值去噪两种方法的优缺点。最后，我们得出结论。

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