# Independent Component Analysis based on multiple data-weighting

@article{Bedychaj2019IndependentCA, title={Independent Component Analysis based on multiple data-weighting}, author={Andrzej Bedychaj and Przemysław Spurek and Lukasz Struski and Jacek Tabor}, journal={ArXiv}, year={2019}, volume={abs/1906.00028} }

Independent Component Analysis (ICA) - one of the basic tools in data analysis - aims to find a coordinate system in which the components of the data are independent. In this paper we present Multiple-weighted Independent Component Analysis (MWeICA) algorithm, a new ICA method which is based on approximate diagonalization of weighted covariance matrices. Our idea is based on theoretical result, which says that linear independence of weighted data (for gaussian weights) guarantees independence… Expand

#### One Citation

WICA: nonlinear weighted ICA

- Computer Science
- ArXiv
- 2020

A new nonlinear ICA model is constructed, called WICA, which obtains better and more stable results than other algorithms and a crucial tool is given by a new efficient method of verifying nonlinear dependence with the use of computation of correlation coefficients for normally weighted data. Expand

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