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IJON
2006
127views more  IJON 2006»
13 years 4 months ago
Sparse ICA via cluster-wise PCA
In this paper, it is shown that Independent Component Analysis (ICA) of sparse signals (sparse ICA) can be seen as a cluster-wise Principal Component Analysis (PCA). Consequently,...
Massoud Babaie-Zadeh, Christian Jutten, Ali Mansou...
IJON
2006
117views more  IJON 2006»
13 years 4 months ago
EEG classification using generative independent component analysis
We present an application of Independent Component Analysis (ICA) to the discrimination of mental tasks for EEG-based Brain Computer Interface systems. ICA is most commonly used w...
Silvia Chiappa, David Barber
BMCBI
2006
129views more  BMCBI 2006»
13 years 4 months ago
Independent Component Analysis-motivated Approach to Classificatory Decomposition of Cortical Evoked Potentials
Background: Independent Component Analysis (ICA) proves to be useful in the analysis of neural activity, as it allows for identification of distinct sources of activity. Applied t...
Tomasz G. Smolinski, Roger Buchanan, Grzegorz M. B...
ICASSP
2010
IEEE
13 years 4 months ago
Reverberated speech signal separation based on regularized subband feedforward ICA and instantaneous direction of arrival
In this paper, independent component analysis (ICA) in a subband domain has been extended into a feed-forward network. The feed-forward network maximizes mutual independence of se...
Lae-Hoon Kim, Ivan Tashev, Alex Acero
ICA
2010
Springer
13 years 5 months ago
Adaptive Underdetermined ICA for Handling an Unknown Number of Sources
Independent Component Analysis is the best known method for solving blind source separation problems. In general, the number of sources must be known in advance. In many cases, pre...
Andreas Sandmair, Alam Zaib, Fernando Puente Le&oa...
ESANN
2006
13 years 6 months ago
Non-orthogonal Support Width ICA
Independent Component Analysis (ICA) is a powerful tool with applications in many areas of blind signal processing; however, its key assumption, i.e. the statistical independence o...
John Aldo Lee, Frédéric Vrins, Miche...
ICONIP
2007
13 years 6 months ago
Discovery of Linear Non-Gaussian Acyclic Models in the Presence of Latent Classes
Abstract. An effective way to examine causality is to conduct an experiment with random assignment. However, in many cases it is impossible or too expensive to perform controlled ...
Shohei Shimizu, Aapo Hyvärinen
ICA
2007
Springer
13 years 8 months ago
Compact Representations of Market Securities Using Smooth Component Extraction
Independent Component Analysis (ICA) is a statistical method for expressing an observed set of random vectors as a linear combination of statistically independent components. This...
Hariton Korizis, Nikolaos Mitianoudis, Anthony G. ...
ICANN
2003
Springer
13 years 9 months ago
Dimension Reduction Based on Orthogonality - A Decorrelation Method in ICA
In independent component analysis problems, when we use a one-unit objective function to iteratively estimate several independent components, the uncorrelatedness between the indep...
Kun Zhang, Lai-Wan Chan
ICA
2004
Springer
13 years 10 months ago
ICA Using Kernel Entropy Estimation with NlogN Complexity
Abstract. Mutual information (MI) is a common criterion in independent component analysis (ICA) optimization. MI is derived from probability density functions (PDF). There are scen...
Sarit Shwartz, Michael Zibulevsky, Yoav Y. Schechn...