Complex-valued differential operator-based method for multi-component signal separation

doi:10.1016/j.sigpro.2016.09.015

CORC > 自动化研究所 > 中国科学院自动化研究所 > 智能制造技术与系统研究中心 > 多维数据分析团队

	Complex-valued differential operator-based method for multi-component signal separation
	Guo, Baokui1 ; Peng, Silong1 ; Hu, Xiyuan1 ; Xu, Pengcheng 2
刊名	SIGNAL PROCESSING
	2017-03-01
卷号	132 期号:2017 页码:66-76
关键词	Operator-based Signal Separation Null Space Pursuit Complex-valued Differential Operator Empirical Mode Decomposition Synchrosqueezing Wavelet Transform Am-fm Signal
DOI	10.1016/j.sigpro.2016.09.015
文献子类	Article
英文摘要	The null space pursuit (NSP) algorithm is an operator-based signal separation approach which separates a signal into a set of additive subcomponents using adaptively estimated operators and parameters. In this paper, a new operator termed complex-valued differential (CD) operator is proposed. Combining with the CD operator, this paper proposes NSP-CD algorithm to solve the CD operator-based signal separation problem. The NSP-CD algorithm can separate the multi-component signal into sum of amplitude-modulated and frequency-modulated (AM-FM) signals in the form of A(t)exp(j)(0). The proposed NSP-CD algorithm has many advantages. Firstly, the proposed CD operator can ensure that the AM FM signal totally lies in the null space of the operator rather than close to the null space that the original used operator may reach. Secondly, compared with the original NSP algorithm, our algorithm provides a more reasonable strategy to update the regularization parameter lambda and the leakage factor gamma. Finally, we have proved that the proposed algorithm has quadric convergence theoretically. Experiments on both synthetic and real-life signals demonstrate that the NSP-CD algorithm is more robust and effective than other state-of-the-art methods.
WOS关键词	EMPIRICAL MODE DECOMPOSITION ; COMPONENT ANALYSIS ; REPRESENTATIONS ; REASSIGNMENT ; ALGORITHM
WOS研究方向	Engineering
语种	英语
WOS记录号	WOS:000389294600007
资助机构	Natural Science Foundation of China(61571438)
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/13372]
专题	自动化研究所_智能制造技术与系统研究中心_多维数据分析团队
通讯作者	Hu, Xiyuan
作者单位	1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Guo, Baokui,Peng, Silong,Hu, Xiyuan,et al. Complex-valued differential operator-based method for multi-component signal separation[J]. SIGNAL PROCESSING,2017,132(2017):66-76.
APA	Guo, Baokui,Peng, Silong,Hu, Xiyuan,&Xu, Pengcheng.(2017).Complex-valued differential operator-based method for multi-component signal separation.SIGNAL PROCESSING,132(2017),66-76.
MLA	Guo, Baokui,et al."Complex-valued differential operator-based method for multi-component signal separation".SIGNAL PROCESSING 132.2017(2017):66-76.