太赫兹科学与电子信息学报2024，Vol.22Issue(2)：194-200,7.DOI:10.11805/TKYDA2021426
基于EMD-NLPCA的欠定非线性盲源分离算法及应用
Research and application of EMD-NLPCA algorithm
唐铭阳 1吴亚锋 1李晋1
作者信息
- 1. 西北工业大学 能源与动力学院,陕西 西安 710129
- 折叠
摘要
Abstract
A Blind Source Separation(BSS)algorithm based on Empirical Mode Decomposition-Non-Linear Principal Component Analysis(EMD-NLPCA)is proposed after studying the BSS algorithm for underdetermined non-linear mixed signals.Firstly,EMD is applied to the observed signal,then high-order statistics are introduced after reconstructing the signal.The principal component analysis is carried out to complete the signal separation.This algorithm can not only deal with the undetermined environment but also solve the problem of non-linear mixing.In the simulation,the results of the algorithm are compared with those of the sparse component analysis,which proves that the proposed algorithm is correct and more universal than the sparse component analysis.Finally,the algorithm is applied to the separation of driving audio signals of unmanned aerial vehicle engines,and it works well.关键词
盲源分离/经验模式分解/非线性主成分分析/欠定/非线性混合Key words
Blind Source Separation/Empirical Mode Decomposition/Non-Linear Principal Component Analysis/underdetermined/non-linear mixed分类
信息技术与安全科学引用本文复制引用
唐铭阳,吴亚锋,李晋..基于EMD-NLPCA的欠定非线性盲源分离算法及应用[J].太赫兹科学与电子信息学报,2024,22(2):194-200,7.
