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Blind source separation of more sources than mixtures using sparse mixture models
Shi, ZW; Tang, HW; Tang, YY
2005-12-01
Source PublicationPATTERN RECOGNITION LETTERS
ISSN0167-8655
SubtypeArticle
Volume26Issue:16Pages:2491-2499
AbstractIn this paper, blind source separation is discussed with more sources than mixtures. This blind separation technique assumes a linear mixing model and involves two steps: (1) learning the mixing matrix for the observed data using the sparse mixture model and (2) inferring the sources by solving a linear programming problem after the mixing matrix is estimated. Through the experiments of the speech signals, we demonstrate the efficacy of this proposed approach. (c) 2005 Elsevier B.V. All rights reserved.
Keywordblind source separation overcomplete representation sparse mixture model independent component analysis signal processing
Indexed BySCI
Language英语
WOS IDWOS:000233307200001
Citation statistics
Cited Times:6[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/14064
Collection中国科学院心理研究所回溯数据库(1956-2010)
Affiliation1.Tsinghua Univ, Dept Automat, State Key Lab Intelligent Technol & Syst, Beijing 100084, Peoples R China
2.Dalian Univ Technol, Inst Computat Biol & Bioinformat, Dalian 116023, Peoples R China
3.Dalian Univ Technol, Inst Neuroinformat, Dalian 116023, Peoples R China
4.Chinese Acad Sci, Lab Visual Informat Proc, Beijing 100101, Peoples R China
5.Chinese Acad Sci, Key Lab Mental Hlth, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Shi, ZW,Tang, HW,Tang, YY. Blind source separation of more sources than mixtures using sparse mixture models[J]. PATTERN RECOGNITION LETTERS,2005,26(16):2491-2499.
APA Shi, ZW,Tang, HW,&Tang, YY.(2005).Blind source separation of more sources than mixtures using sparse mixture models.PATTERN RECOGNITION LETTERS,26(16),2491-2499.
MLA Shi, ZW,et al."Blind source separation of more sources than mixtures using sparse mixture models".PATTERN RECOGNITION LETTERS 26.16(2005):2491-2499.
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