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Multilinear independent components analysis - IEEE ...
Abstract: Independent components analysis (ICA) maximizes the statistical independence of the representational components of a training image ensemble, but it cannot distinguish between the different factors, or modes, inherent to image formation, including scene structure, illumination, and imaging. We introduce a nonlinear, multifactor model that generalizes ICA.
Independent Component Analysis edited by Stephen Roberts
Independent Component Analysis (ICA) has recently become an important tool for modelling and understanding empirical datasets. It is a method of separating out independent sources from linearly mixed data, and belongs to the class of general linear models.
 Independent Component Analysis: Algorithms and Applications
The statistical model in Eq. 4 is called independent component analysis, or ICA model. The ICA model is a generative model, which means that it describes how the observed data are generated by a process of mixing the components si. The independent components are latent variables, meaning that they cannot be directly observed.
Allassonnière , Younes : A stochastic algorithm for ...
Independent component analysis in statistical shape models. SPIE Medical Image Analysis 375–383. Valpola Lappalainen, H. and Pajunen, P. (2000). Fast algorithms for Bayesian independent component analysis. In Proc. of the Second International Workshop on Independent Component Analysis and Blind Signal Separation, ICA 2000, Helsinki, Finland ......