Institute of Information Theory and Automation

You are here

Bibliography

Monography Chapter

Improved variants of the FastICA algorithm

Koldovský Zbyněk, Tichavský Petr

: Advances in Independent Component Analysis and Learning Machines, p. 53-74 , Eds: Bingham Ella, Kaski Samuel, Laaksonen Jorma, Lampinen Jouko

: GA14-13713S, GA ČR

: independent component analysis, blind source separation, FastICA, efica, Cramer-Rao lower bound

: 10.1016/B978-0-12-802806-3.00002-6

: http://library.utia.cas.cz/separaty/2015/SI/tichavsky-0444036.pdf

(eng): The article presents a survey of improved variants of the famous FastICA algorithm for Independent Component Analysis. Variants of the algorithm tailored to separate mixtures of stationary non-Gaussian signals and mixtures of nonstationary (block-wise stationary) non-Gaussian signals are described. Performance analyses of the algorithms are given and compared to the respective Cramer-Rao lower bounds. The behavior of FastICA variants when additive noise is present in the signal mixture is studied through a bias analysis.

: BB

2019-01-07 08:39