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Investigations on non-Gaussian factor analysis

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3 Author(s)
Zhi-Yong Liu ; Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, China ; Kai-Chun Chiu ; Lei Xu

This letter further explores the Bayesian Ying-Yang learning based non-Gaussian factor analysis (NFA) via investigating its key yet analytically intractable factor estimating step. Among the three suggested numerical approaches we empirically show that the so-called iterative fixed posteriori approximation approach is the most optimal, as well as theoretically prove that the iterative fixed posteriori approximation is another type of EM-algorithm, with the proof of its convergence also shown.

Published in:

Signal Processing Letters, IEEE  (Volume:11 ,  Issue: 7 )