Blind source separation of more sources than mixtures using sparse mixture models
Shi, ZW; Tang, HW; Tang, YY
2005-12-01
发表期刊PATTERN RECOGNITION LETTERS
ISSN0167-8655
文章类型Article
卷号26期号:16页码:2491-2499
摘要In 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.
关键词blind source separation overcomplete representation sparse mixture model independent component analysis signal processing
收录类别SCI
语种英语
WOS记录号WOS:000233307200001
引用统计
被引频次:6[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.psych.ac.cn/handle/311026/14064
专题中国科学院心理研究所回溯数据库(1956-2010)
作者单位1.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
推荐引用方式
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.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Shi, ZW]的文章
[Tang, HW]的文章
[Tang, YY]的文章
百度学术
百度学术中相似的文章
[Shi, ZW]的文章
[Tang, HW]的文章
[Tang, YY]的文章
必应学术
必应学术中相似的文章
[Shi, ZW]的文章
[Tang, HW]的文章
[Tang, YY]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。