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ICA
2012
Springer
7 years 11 months ago
A Canonical Correlation Analysis Based Method for Improving BSS of Two Related Data Sets
We consider an extension of ICA and BSS for separating mutually dependent and independent components from two related data sets. We propose a new method which first uses canonical...
Juha Karhunen, Tele Hao, Jarkko Ylipaavalniemi
ICASSP
2011
IEEE
8 years 7 months ago
Separating sources from sequentially acquired mixtures of heart signals
In this paper, we consider the problem of separating a set of independent components when only one movable sensor is available to record the mixtures. We propose to exploit the qu...
Fábio de Lima Hedayioglu, Maria G. Jafari, ...
IJON
2002
69views more  IJON 2002»
9 years 3 months ago
From single-trial EEG to brain area dynamics
We here present a new technique for visualizing the temporal dynamics of brain area activation and interaction at high-temporal resolution. We
Arnaud Delorme, Scott Makeig, Michèle Fabre...
NN
2000
Springer
159views Neural Networks» more  NN 2000»
9 years 3 months ago
Independent component analysis for noisy data -- MEG data analysis
ICA (independent component analysis) is a new, simple and powerful idea for analyzing multi-variant data. One of the successful applications is neurobiological data analysis such ...
Shiro Ikeda, Keisuke Toyama
JCP
2007
100views more  JCP 2007»
9 years 3 months ago
Extraction of Unique Independent Components for Nonlinear Mixture of Sources
—In this paper, a neural network solution to extract independent components from nonlinearly mixed signals is proposed. Firstly, a structurally constrained mixing model is introd...
Pei Gao, Li Chin Khor, Wai Lok Woo, Satnam Singh D...
IJON
2006
131views more  IJON 2006»
9 years 3 months ago
Optimizing blind source separation with guided genetic algorithms
This paper proposes a novel method for blindly separating unobservable independent component (IC) signals based on the use of a genetic algorithm. It is intended for its applicati...
J. M. Górriz, Carlos García Puntonet...
ICA
2010
Springer
9 years 4 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...
NIPS
2004
9 years 5 months ago
Linear Multilayer Independent Component Analysis for Large Natural Scenes
In this paper, linear multilayer ICA (LMICA) is proposed for extracting independent components from quite high-dimensional observed signals such as large-size natural scenes. Ther...
Yoshitatsu Matsuda, Kazunori Yamaguchi
DAGM
2006
Springer
9 years 7 months ago
Robust MEG Source Localization of Event Related Potentials: Identifying Relevant Sources by Non-Gaussianity
Independent Component Analysis (ICA) is a frequently used preprocessing step in source localization of MEG and EEG data. By decomposing the measured data into maximally independent...
Peter Breun, Moritz Grosse-Wentrup, Wolfgang Utsch...
CDC
2009
IEEE
155views Control Systems» more  CDC 2009»
9 years 7 months ago
Improved independent component regression modeling
The conventional independent component regression (ICR), as an exclusive two-step implementation algorithm, has the risk similar to principal component regression (PCR). That is, t...
Chunhui Zhao, Furong Gao, Tao Liu, Fuli Wang
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