计算机工程与科学2017，Vol.39Issue(4)：763-768,6.DOI:10.3969/j.issn.1007-130X.2017.04.021
基于EEMD和模糊阈值的去噪方法
EEMD and fuzzy threshold based noise suppression
摘要
Abstract
In order to improve the denoising effect of the noise dominant mode in EEMD decomposition,we propose a novel denoising method combining the EEMD and fuzzy threshold by using fuzzy membership degree.Firstly,the similarity between the intrinsic density function (IMF) and the probability density function (PDF) of the observed signals is calculated using the two norms,and the noisedominated IMF is obtained.Then,the noise-dominated IMF is subjected to fuzzy threshold processing and hence the noise is removed from the IMF.Finally,all of the remained IMFs are reconstructed to get noise suppression signals.Simulation experiments are conducted by using both suppositional and ECG signals.The results show that the denoising effect of the proposed method is better than that of the wavelet half-soft threshold method and the EMD-based interval threshold (EMD-IT) method.关键词
聚合经验模态分解/本征模态函数/模糊隶属度/噪声主导模态/信号去噪Key words
ensemble empirical mode decomposition/intrinsic mode function/fuzzy membership degree/noise dominant mode/signal denoising分类
信息技术与安全科学引用本文复制引用
马子骥,郭帅锋,刘宏立,李艳福,倪忠..基于EEMD和模糊阈值的去噪方法[J].计算机工程与科学,2017,39(4):763-768,6.基金项目
中央国有资本经营预算项目(财企[2013]470号) （财企[2013]470号）
中央高校基本科研项目(2014-004) （2014-004）
国家自然科学基金(61172089) （61172089）
湖南省科技计划项目(2014WK3001) （2014WK3001）
中国博士后科研基金(2014M562100) （2014M562100）
湖南省科技计划重点项目(2015JC3053) （2015JC3053）
