A Cascaded Adaptive Local Projection Denoising Method

doi:10.12068/j.issn.1005-3026.2022.03.009

Abstract

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

CLC Number:

TP391.4

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.

References

[1]Liu L，Wang Y，Li Y，et al.Noise robust method for analytically solvable chaotic signal reconstruction［J］.Circuits，Systems，and Signal Processing，2019，38:4096-4114.
[2]Ma X，Zhang D，Zhang Y.Novel noise reduction method based on improved empirical wavelet transform and kurtosis for partial discharge signal of high-voltage cables［J］.The Journal of Engineering，2020，11:1088-1094.
[3]Assi E B，Nguyen D K，Rihana S，et al.Towards accurate prediction of epileptic seizures:a review［J］.Biomedical Signal Processing and Control，2017，34:144-157.
[4]Bortolan G，Christov I，Simova I，et al.Noise processing in exercise ECG stress test for the analysis and the clinical characterization of QRS and T wave alternans［J］.Biomedical Signal Processing & Control，2015，18:378-385.
[5]Takens F.Detecting strange attractors in turbulence［J］.Lecture Notes in Math，1981，898:366-381.
[6]Przybyla T，Pander T.Modified neighborhood determination in nonlinear state-space projective filtering［C］//25th International Conference “Mixed Design of Integrated Circuits and System”(MIXDES).New York:IEEE，2018:376-380.
[7]Molaie M，Jafari S，Moradi M H，et al.A chaotic viewpoint on noise reduction from respiratory sounds［J］.Biomedical Signal Processing & Control，2014，10:245-249.
[8]Moore J M，Small M，Karrech A.Improvements to local projective noise reduction through higher order and multiscale refinements［J］.Chaos，2015，25(6):653-671.
[9]Chen M Y，Fang Y H，Zheng X F.Phase space reconstruction for improving the classification of single trial EEG［J］.Biomedical Signal Processing and Control，2014，11:10-16.
[10]Sun J F，Zhao Y，Zhang J，et al.Reducing colored noise for chaotic time series in the local phase space［J］.Physical Review E，2007，76(2):026211.
[11]Rainer H，Kantz H，Matassini L，et al.Noise reduction for human speech signals by local projections in embedding spaces［J］.IEEE Transactions on Circuits & Systems Part I:Fundamental Theory & Applications，2001，48(12):1454-1461.
[12]Przybya T，Kotas M，Ski J.On clustering based nonlinear projective filtering of biomedical signals［J］.Biomedical Signal Processing and Control，2018，44:237-246.
[13]Chelidze D.Smooth local subspace projection for nonlinear noise reduction［J］.Chaos，2014，24(1):1752-1762.
[14]Huang N E，Shen Z，Long S R，et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis［J］.Proceedings of Mathematical Physical & Engineering Sciences，1998，454:903-995.
[15]杨望灿，张培林，张云强.基于邻域自适应局部保持投影的轴承故障诊断模型［J］.振动与冲击，2014，33(1):39-44.(Yang Wang-can，Zhang Pei-lin，Zhang Yun-qiang.Bearing fault diagnosis model based on neighborhood adaptive local preserving projection［J］.Journal of Vibration and Shock，2014，33(1):39-44.)
[16]孟会杰，陈双全，王润秋.基于局部投影法的微地震信号识别［C］//中国石油学会2017年物探技术研讨会论文集.天津，2017:961-964.(Meng Hui-jie，Chen Shuang-quan，Wang Run-qiu.Microseismic signal recognition based on local projection method［C］//Proceedings of 2017 Geophysical Technology Seminar of China Petroleum Society.Tianjin，2017:961-964.)
[17]梁庆真，郭兴明，袁志会.局部投影和离散小波变换在心音信号去噪中的应用［J］.振动与冲击，2014，33(13):188-193.(Liang Qing-zhen，Guo Xing-ming，Yuan Zhi-hui.Application of local projection and discrete wavelet transform in heart sound signal denoising［J］.Journal of Vibration and Shock，2014，33(13):188-193.)
[18]胥永刚，赵国亮，马朝永，等.基于双树复小波与非线性时间序列的降噪方法［J］.振动与冲击，2015，34(16):135-140.(Xu Yong-gang，Zhao Guo-liang，Ma Chao-yong，et al.Noise reduction method based on dual tree complex wavelet and nonlinear time series［J］.Journal of Vibration and Shock，2015，34(16):135-140.)
[19]Tang G，Yan X，Wang X，et al.Chaotic signal denoising based on adaptive smoothing multiscale morphological filtering［J］.Complexity，2020:7242943.doi:10.1155/2020/7242943.
[20]Wan X，Iwata K，Riera J，et al.Artifact reduction for EEG/fMRI recording:nonlinear reduction of ballistocardiogram artifacts［J］.Clinical Neuro Physiology，2018，117(3):68-80.
[21]Kim H S，Eykholt R，Salas J D.Nonlinear dynamics，delay times，and embedding windows［J］.Physical D:Nonlinear Phenomena，1999，127(1):668-680.
[22]Araki S J，Koo J W，Martin R S，et al.A grid-based nonlinear approach to noise reduction and deconvolution for coupled systems—science direct［J］.Physical D:Nonlinear Phenomena，2021，417:132819.
[23]Johnson M T，Povinelli R J.Generalized phase space projection for nonlinear noise reduction［J］.Physical D:Nonlinear Phenomena，2005，201(3/4):306-317.
[24]Xu B X，Liu R X，Shu M L，et al.An ECG denoising method based on the generative adversarial residual network［J］.Computational and Mathematical Methods in Medicine，2021:5527904.doi:10.1155/2021/5527904.
[25]韩敏，刘玉花，史志伟，等.改进局部投影算法的混沌降噪研究［J］.系统仿真学报，2007，19(2):364-368.(Han Min，Liu Yu-hua，Shi Zhi-wei，et al.Research on chaotic noise reduction based on improved local projection algorithm［J］.Journal of System Simulation，2007，19(2):364-368.)
[26]冯龙飞，高建民，高智勇，等.基于LP与小波包的复杂机电系统监测序列混沌降噪方法［J］.振动与冲击，2020，39(7):1-7.(Feng Long-fei，Gao Jian-min，Gao Zhi-yong，et al.Chaotic noise reduction method for monitoring sequence of complex electromechanical system based on LP and wavelet packet［J］.Journal of Vibration and Shock，2020，39(7):1-7.)
[27]Kantz H，Schreiber T.Nonlinear time series analysis［M］.New York:Cambridge University Press，2004:180-185.
[28]Kotas M.Robust projective filtering of time-warped ECG beats［J］.Computer Methods & Programs in Biomedicine，2008，92(2):161-172.