计算机工程与科学2017，Vol.39Issue(5)：919-924,6.DOI:10.3969/j.issn.1007-130X.2017.05.015
基于奇异谱分析的经验模态分解去噪方法
An empirical mode decomposition de-noising method based on singular spectrum analysis
摘要
Abstract
We propose an empirical mode decomposition (EMD) de-noising method based on singular spectrum analysis (SA).Firstly,noisy signals are decomposed into several intrinsic mode functions (IMF) by the EMD in this method.The first IMF is regarded as high-frequency noise and the noise energy included in other IMFs can be estimated.Then,the ratio of signal energy in each IMF can be calculated.Secondly,the SSA is implemented on each IMF with proper window length and parts of proper singular value decomposition (SVD) components are selected to reconstruct the IMF according to the ratio of signal energy in each IMF.Finally,the denoised signals are obtained by adding all the reconstructed IMF and the residue.Compared with the wavelet soft threshold method,the EMD soft threshold method and the EMD filter method,the proposed method is superior to other methods as a whole,so it is an effective signal de-noising method.关键词
经验模态分解/奇异谱分析/本征模态函数Key words
empirical mode decomposition/singular spectrum analysis/intrinsic mode function分类
信息技术与安全科学引用本文复制引用
肖小兵,刘宏立,马子骥..基于奇异谱分析的经验模态分解去噪方法[J].计算机工程与科学,2017,39(5):919-924,6.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）
