Estimation of Power Spectrum by Using M-transform andWavelet Shrinkage
Estimation of Power Spectrum by Using M-transform andWavelet Shrinkage
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利用M变换和小波收缩估计功率谱
DOI：
10.1109/sice.2006.315295
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发表时间：
2006
期刊：
影响因子：
--
通讯作者：
K. Kaba
中科院分区：
文献类型：
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作者：
H. Harada;Su;H. Kashiwagi;K. Kaba
作者最近提出了一种新的信号处理技术，称为M变换。通过使用M变换，脉冲噪声被转换成一个小幅度的随机信号。本文还提出了一种对M变换后的信号进行小波收缩，同时去除混合脉冲噪声和白色噪声的新方法。该方法能有效去除脉冲噪声和白色噪声的混合噪声。本文将噪声抑制方法应用于功率谱的估计。利用输入信号和输出信号的功率谱可以得到线性系统的频率传递函数。在实际测量频率传递函数时，必须用周期图代替输入信号的互谱和功率谱。由于周期图波动很大，估计的频率传递函数包含脉冲噪声。为了去除这些噪声，我们使用所提出的降噪方法。从计算机仿真的结果来看，即使在存在正弦噪声的情况下，也能够推测出信号
The authors have recently proposed a new signal processing technique called M-transform. By using the M-transform, an impulsive noise is converted into a small-amplitude random signal. We also proposed a new method to remove mixed impulsive noise and white noise simultaneously by applying the wavelet shrinkage to the M-transformed signal. The proposed method was very efficient to remove mixed impulsive and white noise. In this paper, we apply the noise reduction method to estimation of a power spectrum. Frequency transfer function of a linear system can be obtained by using the power spectrum of the input signal and the output signal. In the actual measurement of the frequency transfer function, we must use a periodogram instead of the cross-spectrum and the power spectrum of the input signal. Since the periodogram fluctuates greatly, the estimated frequency transfer function includes impulsive noises. In order to remove these noises, we use the proposed noise reduction method. From the result of the computer simulation, the signal was able to be presumed even when the sinusoidal noise existed