级联自适应局部投影降噪方法

doi:10.12068/j.issn.1005-3026.2022.03.009

东北大学学报（自然科学版） ›› 2022, Vol. 43 ›› Issue (3): 368-375.DOI: 10.12068/j.issn.1005-3026.2022.03.009

级联自适应局部投影降噪方法

徐礼胜^1,2，崔慧颖¹，吴俊鼎¹，王仲怡¹

(1. 东北大学医学与生物信息工程学院，辽宁沈阳110169; 2. 沈阳东软智能医疗科技研究院有限公司，辽宁沈阳110167)

修回日期:2021-05-09 接受日期:2021-05-09 发布日期:2022-05-18
通讯作者: 徐礼胜
作者简介:徐礼胜(1975-)，男，安徽安庆人，东北大学教授，博士生导师.
基金资助:
国家自然科学基金资助项目(61773110); 中央高校基本科研业务费专项资金资助项目(N2119008); 沈阳东软智能医疗科技研究院有限公司会员课题基金资助项目(MCMP062002).

A Cascaded Adaptive Local Projection Denoising Method

XU Li-sheng^1,2， CUI Hui-ying¹， WU Jun-ding¹， WANG Zhong-yi¹

1. College of Medicine and Biological Information Engineering， Northeastern University， Shenyang 110169， China; 2. Neusoft Research of Intelligent Healthcare Technology， Co. Ltd.， Shenyang 110167， China.

Revised:2021-05-09 Accepted:2021-05-09 Published:2022-05-18
Contact: XU Li-sheng
About author:-
Supported by:
-

摘要/Abstract

摘要： 针对具有非线性、非平稳性特征的信号，提出一种邻域半径自适应局部投影和小波阈值去噪级联的降噪方法.首先，利用经验模态分解得到信号中的高频分量并以此估计噪声水平;再根据噪声水平确定邻域半径;最后，利用该半径进行局部投影处理并结合小波阈值方法进行细节平滑.Lorenz系统时间序列的降噪结果表明，本方法能够提高信噪比并降低均方误差，并在信号结构失真时恢复其原始吸引子形态，去噪和还原信号特征的能力皆优于小波阈值去噪方法.对桡、颈、肱动脉脉搏信号、心电信号的降噪结果展示了本方法在生理信号噪声抑制和特征保留方面的优越性能.

关键词: 自适应邻域选取;局部投影算法;小波阈值降噪;Lorenz系统;生理信号

Abstract: For signals with nonlinear and nonstationary characteristics， denoising method based on the cascade of neighborhood radius adaptive local projection and wavelet threshold denoising was proposed. Firstly， the high-frequency component of the signal was obtained by empirical mode decomposition(EMD)， and the noise level was estimated. Then， the neighborhood radius was determined according to the noise level. Finally， the radius was used for local projection processing and combined with wavelet threshold method for detail smoothing. The denoising results of Lorenz system time series show that this method can improve the signal-to-noise ratio， reduce the mean square error and restore the original attractor shape when the signal structure is distorted. The ability of the proposed method in denoising and restoring the signal characteristics is better than that of the wavelet threshold denoising method. The denoising results of radial， carotid and brachial artery pulse signals and electrocardiogram(ECG)signals show the superior performance of this method in physiological signal noise suppression and feature retention.

Key words: adaptive neighborhood selection; local projection algorithm; wavelet threshold denoising; Lorenz system; physiological signals

中图分类号:

TP391.4

徐礼胜，崔慧颖，吴俊鼎，王仲怡. 级联自适应局部投影降噪方法[J]. 东北大学学报（自然科学版）, 2022, 43(3): 368-375.

XU Li-sheng， CUI Hui-ying， WU Jun-ding， WANG Zhong-yi. A Cascaded Adaptive Local Projection Denoising Method[J]. Journal of Northeastern University(Natural Science), 2022, 43(3): 368-375.

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级联自适应局部投影降噪方法

A Cascaded Adaptive Local Projection Denoising Method

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