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脉搏信号包含大量的噪声,具有强烈的非线性和非平稳性。针对传统的小波变换去噪算法的缺陷,本文提出了一种基于双树复小波变换和形态滤波的去噪算法,具有结构简单、数学含义清晰及计算复杂度低等优点,有效的克服了离散小波变换的平移敏感性和频率混淆。实验表明,该算法可以有效的去除脉搏信号中工频干扰及肌电干扰等高频噪声,其信噪比及均方差等定量指标均明显优于传统的阈值去噪算法,能得到较干净的脉搏信号波形。
Pulse signal contains a lot of noise, with strong nonlinear and non-stationary. Aiming at the shortcomings of the traditional wavelet transform denoising algorithm, this paper presents a de-noising algorithm based on double-tree complex wavelet transform and morphological filtering, which has the advantages of simple structure, clear mathematical meaning and low computational complexity, effectively overcoming the discrete Transform sensitivity and frequency confusion of wavelet transform. Experiments show that this algorithm can effectively remove the high-frequency noise such as power frequency interference and electromyography interference in the pulse signal, and its quantitative indexes such as signal-to-noise ratio and mean square error are significantly better than the traditional threshold denoising algorithm, Pulse signal waveform.