DocumentCode :
2331982
Title :
Normalized Information Theoretic Criteria for Blind Signal Extraction
Author :
Cruces, Sergio ; Durán, Iván
Author_Institution :
Teoria de la Serial y Comunicaciones, Seville Univ.
Volume :
5
fYear :
2006
fDate :
14-19 May 2006
Abstract :
In this paper we present new normalized criteria for the extraction of the scaled sources whose density have the minimum support measure or the minimum entropy. Both criteria are part of a more general entropy minimization principle based on Renyi´s entropies. However, the proposed approach (based on Renyi´s entropies or orders zero and one) have some special advantages, which allow to relax the assumption of having identically distributed source signals
Keywords :
blind source separation; feature extraction; minimum entropy methods; blind signal extraction; distributed source signals; minimum entropy; normalized information theoretic criteria; Biomedical measurements; Biomedical signal processing; Data mining; Deconvolution; Density measurement; Digital communication; Digital signal processing; Entropy; Independent component analysis; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
Conference_Location :
Toulouse
ISSN :
1520-6149
Print_ISBN :
1-4244-0469-X
Type :
conf
DOI :
10.1109/ICASSP.2006.1661345
Filename :
1661345
Link To Document :
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