计算机应用与软件2013，Vol.30Issue(8)：170-173,4.DOI:10.3969/j.issn.1000-386x.2013.08.045
一种自适应单入多出盲源分离方法
A SELF-ADAPTIVE ALGORITHM FOR SINGLE INPUT MULTIPLE OUT BLIND SOURCE SEPARATION
摘要
Abstract
Single input multiple out blind source separation (SIM0_BSS) is a special kind of underdetermined blind source separation.In the process of existing algorithms,too much personal experience is required in judging,and the self-adaptability is poor.To address this problem,we propose that first the ensemble empirical mode decomposition (EEMD) is used to decompose the single-channel signal which is the mixture of multi-channel signals into multi-channel intrinsic mode functions (IMSs) ; then,the principal component analysis is applied to reduce the dimensionality of multi-channel IMFs adaptively,meanwhile the independent component analysis is used to restore the mutualindependent multiple source signals.Finally,the simulation is conducted on periodic mixed signal and biological mixed signal,the simulation results indicate that the proposed algorithm has quick speed with good separation effect than the EEMD_ICA algorithm under different NSR conditions.关键词
单入多出盲源分离/总体经验模态分解/主成分分析/独立成分分析/MatlabKey words
Single input multiple out blind source separation / Ensemble empirical mode decomposition / Principal component analysis/Independent component analysis / Matlab分类
信息技术与安全科学引用本文复制引用
黄书华,卓东风,郭一娜..一种自适应单入多出盲源分离方法[J].计算机应用与软件,2013,30(8):170-173,4.基金项目
山西省回国留学人员科研资助项目(编号92)(20101069) （编号92）
山西省人力资源与社会保障厅山西省留学人员科技活动项目(20121030) （20121030）
山西省科技厅山西省国际科技合作计划项目(2012081036) （2012081036）
太原市科技局大学生创新创业专项(120164034). （120164034）
