摘要
为去除脉搏信号中的噪声,提出了一种将自适应噪声完备集合经验模态分解(complete ensemble empirical mode decomposition with adaptive noise,CEEMDAN)和排列熵(permutation entropy,PE)相结合的方法。首先由HK-2000C脉搏信号传感器采集信号,对采集的脉搏信号用CEEMDAN得到一系列的本征模态分量(intrinsic mode function,IMF);然后计算各个本征模态分量的排列熵值,根据排列熵值选定阈值,确定并处理代表噪声的本征模态分量;最后对处理后的模态分量进行重构,从而消除脉搏信号中的噪声。实验结果表明,与经验模态分解(empirical mode decomposition,EMD)去噪方法和集合经验模态分解(ensemble empirical mode decomposition,EEMD)去噪方法相比,所提方法对脉搏信号去噪的效果更好。
In order to remove the noise of the pulse signal,a new method is proposed by combining complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)and permutation entropy(PE).The signal is collected by the HK-2000 C pulse sensors.A series of intrinsic mode function(IMF)are obtained by decomposing the pulse signal with CEEMDAN.Then,the permutation entropy of each IMF is calculated.The threshold value is selected according to the PE to determine and process the mode functions which is regarded as noise.The processed intrinsic mode functions are reconstructed so as to eliminate the noise effectively.The experiment results show that this method has better performance in pulse signal de-noising than the empirical mode decomposition(EMD)method and ensemble empirical mode decomposition(EEMD)method.
作者
张红
王龙
李小娜
ZHANG Hong;WANG Long;LI Xiaona(College of Communication and Information Engineering, Xi’an University ofScience and Technology, Xi’an 710054, China)
出处
《中国科技论文》
CAS
北大核心
2019年第3期250-254,共5页
China Sciencepaper
基金
榆林市科学技术局项目(2016-17-4)
西安科技大学教育教学改革与研究项目(JG16038)
关键词
脉搏信号
噪声
自适应噪声完备集合经验模态分解
排列熵
pulse signal
noise
complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)
permutation entropy(PE)
