DocumentCode :
1303136
Title :
Blind identification and separation of convolutively mixed independent sources
Author :
Wang, Jun ; He, Zhenya
Author_Institution :
Dept. of Radio Eng., Southeast Univ., Nanjing, China
Volume :
33
Issue :
3
fYear :
1997
fDate :
7/1/1997 12:00:00 AM
Firstpage :
997
Lastpage :
1002
Abstract :
A trispectra method for solving the m-input n-output (n≥m) wideband blind identification and signal separation problem with unknown number of sources m is presented. The method is universal in the sense that it does not impose any restriction on the probability distribution of the input signals provided that they are non-Gaussian. A criterion, which states a sufficient condition for identification and separation, has been proved. An algorithm is also developed based on the criterion, whose efficiency is verified by the simulations.
Keywords :
convolution; identification; probability; signal detection; spectral analysis; blind identification; convolutively mixed independent sources; m-input n-output problem; probability distribution; signal separation problem; trispectra method; Finite impulse response filter; MIMO; Maximum likelihood estimation; Probability distribution; Sensor phenomena and characterization; Signal processing algorithms; Source separation; Speech enhancement; Sufficient conditions; Wideband;
fLanguage :
English
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9251
Type :
jour
DOI :
10.1109/7.599323
Filename :
599323
Link To Document :
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