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Published in:
2010 | OriginalPaper | Chapter
Semi-nonnegative Independent Component Analysis: The (3,4)-SENICAexp Method
Authors : Julie Coloigner, Laurent Albera, Ahmad Karfoul, Amar Kachenoura, Pierre Comon, Lotfi Senhadji
Published in: Latent Variable Analysis and Signal Separation
Publisher: Springer Berlin Heidelberg
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To solve the Independent Component Analysis (ICA) problem under the constraint of nonnegative mixture, we propose an iterative algorithm, called (3,4)-SENICA
exp
. This method profits from some interesting properties enjoyed by third and fourth order statistics in the presence of mixed independent processes, imposing the nonnegativity of the mixture by means of an exponential change of variable. This process allows us to obtain an unconstrained problem, optimized using an ELSALS-like procedure. Our approach is tested on synthetic magnetic resonance spectroscopic imaging data and compared to two existing ICA methods, namely SOBI and CoM2.