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Complex-valued differential operator-based method for multi-component signal separation
Guo, Baokui1; Peng, Silong1; Hu, Xiyuan1; Xu, Pengcheng2
2017-03-01
Source PublicationSIGNAL PROCESSING
ISSN0165-1684
Volume132Pages:66-76
AbstractThe 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.
KeywordOperator-based signal separation Null space pursuit Complex-valued differential operator Empirical mode decomposition Synchrosqueezing wavelet transform AM-FM signal
DOI10.1016/j.sigpro.2016.09.015
Language英语
Funding ProjectNatural Science Foundation of China[61571438]
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000389294600007
PublisherELSEVIER SCIENCE BV
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/24346
Collection应用数学研究所
Affiliation1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
Recommended Citation
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,2017,132:66-76.
APA Guo, Baokui,Peng, Silong,Hu, Xiyuan,&Xu, Pengcheng.(2017).Complex-valued differential operator-based method for multi-component signal separation.SIGNAL PROCESSING,132,66-76.
MLA Guo, Baokui,et al."Complex-valued differential operator-based method for multi-component signal separation".SIGNAL PROCESSING 132(2017):66-76.
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