DocumentCode
3345476
Title
EAMUSE: an extended algorithm for multiple sources extraction
Author
Liang, Ying-Chang ; Li, Yan-Da ; Zhang, Xian-Da
Author_Institution
Dept. of Autom., Tsinghua Univ., Beijing, China
Volume
3
fYear
1995
fDate
30 Apr-3 May 1995
Firstpage
2269
Abstract
This paper addresses the problem of multiple source signals separation in noise. As contrasted to the reported studies in which white noise in different sensors with same noise covariance was assumed, the additive noise sensors considered in this paper have different noise covariance. An extended algorithm for multiple sources extraction (EAMUSE) is proposed. The effectiveness of our approach is demonstrated through standard simulation examples
Keywords
covariance analysis; eigenvalues and eigenfunctions; random noise; signal detection; EAMUSE; additive noise sensors; extended algorithm; multiple sources extraction; noise covariance; signal separation; Adaptive signal processing; Additive noise; Array signal processing; Automation; Noise measurement; Pollution measurement; Signal processing algorithms; Source separation; White noise; Working environment noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1995. ISCAS '95., 1995 IEEE International Symposium on
Conference_Location
Seattle, WA
Print_ISBN
0-7803-2570-2
Type
conf
DOI
10.1109/ISCAS.1995.523881
Filename
523881
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