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ICASSP
2009
IEEE
14 years 7 months ago
Blind sparse source separation for unknown number of sources using Gaussian mixture model fitting with Dirichlet prior
In this paper, we propose a novel sparse source separation method that can be applied even if the number of sources is unknown. Recently, many sparse source separation approaches ...
Shoko Araki, Tomohiro Nakatani, Hiroshi Sawada, Sh...
ISCAS
2005
IEEE
131views Hardware» more  ISCAS 2005»
15 years 3 months ago
Blind signal separation into groups of dependent signals using joint block diagonalization
— Multidimensional or group independent component analysis describes the task of transforming a multivariate observed sensor signal such that groups of the transformed signal com...
Fabian J. Theis
ICASSP
2011
IEEE
14 years 1 months ago
Blind separation of multiple binary sources from one nonlinear mixture
We propose a new method for the blind separation of multiple binary signals from a single general nonlinear mixture. In addition to the usual independence assumption on the input ...
Konstantinos I. Diamantaras, Theophilos Papadimitr...
77
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ESANN
2003
14 years 11 months ago
Comparison of neural algorithms for blind source separation in sensor array applications
- A test bed of experiments with real and artificially generated data has been designed to compare the performance of three well-known algorithms for BSS. The main goal of these ex...
Guillermo Bedoya, Sergio Bermejo, Joan Cabestany
DRM
2005
Springer
15 years 3 months ago
Improved watermark detection for spread-spectrum based watermarking using independent component analysis
This paper presents an efficient blind watermark detection/decoding scheme for spread spectrum (SS) based watermarking, exploiting the fact that in SS-based embedding schemes the ...
Hafiz Malik, Ashfaq A. Khokhar, Rashid Ansari