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