2017/01/31 by Spurek, Przemysław, Tabor, Jacek, Rola, Przemysław +1
#FOS: Mathematics #Statistics Theory (math.ST)
paper · doi:10.48550/arxiv.1701.09160
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. Most of existing methods are based on the minimization of the function of fourth-order moment (kurtosis). Skewness (third-order moment) has received much less attention. In this paper we present a competitive approach to ICA based on the Split Gaussian distribution, which is well adapted to asymmetric data. Consequently, we obtain a method which works better than the classical approaches, especially in the case when the underlying density is not symmetric, which is a typical situation in the color distribution in images.