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» Lattice Independent Component Analysis for fMRI Analysis
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AIPR
2002
IEEE
14 years 2 months ago
ICA Mixture Model based Unsupervised Classification of Hyperspectral Imagery
Conventional remote sensing classification techniques that model the data in each class with a multivariate Gaussian distribution are inefficient, as this assumption is generally ...
Chintan A. Shah, Manoj K. Arora, Stefan A. Robila,...
JMIV
2006
100views more  JMIV 2006»
13 years 9 months ago
Mixed-State Auto-Models and Motion Texture Modeling
In image motion analysis as well as for several application fields like daily pluviometry data modeling, observations contain two components of different nature. A first part is ma...
Patrick Bouthemy, C. Hardouin, Gwenaëlle Piri...
ISBI
2009
IEEE
14 years 4 months ago
EEG Classification by ICA Source Selection of Laplacian-Filtered Data
We studied the performance of a double-spatial filtering method for classification of single-trial electroencephalography (EEG) data that couples the spherical surface Laplacian...
Claudio Carvalhaes, Marcos Perreau Guimaraes, Loga...
NECO
2008
122views more  NECO 2008»
13 years 9 months ago
Constrained Subspace ICA Based on Mutual Information Optimization Directly
We introduce a new approach to constrained Independent Component Analysis (ICA) by formulating the original, unconstrained ICA problem as well as the constraints in mutual informa...
Marc M. Van Hulle
TSP
2008
174views more  TSP 2008»
13 years 9 months ago
Complex ICA Using Nonlinear Functions
We introduce a framework based on Wirtinger calculus for nonlinear complex-valued signal processing such that all computations can be directly carried out in the complex domain. Th...
Tülay Adali, Hualiang Li, Mike Novey, J.-F. C...