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Comparing noise removal in the wavelet and Fourier domains

机译:比较小波和傅立叶域中的噪声去除

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This paper compares time series decomposition in the frequency domain via the discrete Fourier transform to time series decomposition in the wavelet domain via the Wavelet transform for the purpose of signal smoothing and noise removal. The information cost of the signal is computed as a predictor of the performance of the filtering process. Simulations are conducted comparing the frequency domain filter to wavelet domain filters on a variety of signals corrupted with additive Gaussian noise.
机译:本文比较了通过离散傅里叶变换在频域中的时间序列分解与通过小波变换在小波域中的时间序列分解,以达到信号平滑和噪声去除的目的。计算信号的信息成本,作为滤波过程性能的预测指标。进行了仿真,将频域滤波器与小波域滤波器对各种因加性高斯噪声而损坏的信号进行了比较。

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