Name
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. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICASSP.2006.1661345 | 2006 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-13 |
Keywords | Field | DocType |
data mining,blind source separation,digital signal processing,entropy,independent component analysis,deconvolution,vectors,feature extraction | Digital signal processing,Normalization (statistics),Pattern recognition,Deconvolution,Blind signal extraction,Feature extraction,Independent component analysis,Independent and identically distributed random variables,Artificial intelligence,Blind signal separation,Mathematics | Conference |
ISSN | Citations | PageRank |
1520-6149 | 0 | 0.34 |
References | Authors | |
6 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sergio Cruces | 1 | 206 | 19.05 |
| Iván Durán-Díaz | 2 | 21 | 3.85 |