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心电信号去噪的小波消失矩最优选择研究

Study on Optimal Selection of Wavelet Vanishing Moments for ECG Denoising.

机构信息

School of Information Science and Engineering, Central South University, Changsha, 410083, China.

Hunan Vocational College of Commerce, Changsha, 410205, China.

出版信息

Sci Rep. 2017 Jul 4;7(1):4564. doi: 10.1038/s41598-017-04837-9.

Abstract

The frequency characteristics of wavelets and the vanishing moments of wavelet filters are both important parameters of wavelets. Clarifying the relationship between the wavelet frequency characteristics and the vanishing moments of the wavelet filter can provide a theoretical basis for selecting the best wavelet. In this paper, the frequency characteristics of wavelets were analyzed by mathematical modeling, the mathematical relationship between wavelet frequency characteristics and vanishing moments was clarified, the optimal wavelet base function was selected hierarchically according to the amplitude frequency characteristics of ECG signal, and an accurate notch filter was realized according to the frequency characteristics of the noise. The experimental results showed that the optimal orthogonal wavelet analysis for the ECG signals with different frequency characteristics could make the high frequency energy distribution sparser, and the method proposed in this paper could effectively preserve the singularity of the signal and reduce the signal distortion.

摘要

小波的频率特性和小波滤波器的消失矩都是小波的重要参数。阐明小波的频率特性与小波滤波器的消失矩之间的关系,可以为选择最佳小波提供理论依据。本文通过数学建模分析了小波的频率特性,阐明了小波频率特性与消失矩之间的数学关系,根据 ECG 信号的幅频特性,对小波基函数进行分层选择,根据噪声的频率特性实现了准确的陷波滤波器。实验结果表明,对具有不同频率特性的 ECG 信号进行最优正交小波分析,可以使高频能量分布更加稀疏,本文提出的方法可以有效地保持信号的奇异性,减少信号失真。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6140/5496932/8cbd23e4dd7e/41598_2017_4837_Fig1_HTML.jpg

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