The PearsonICA algorithm is a mutual informationbased method for blind separation of statistically independent source signals. It has been shown that the minimization of mutual information leads to iterative use of score functions, i.e. derivatives of log densities. The Pearson system allows adaptive modeling of score functions. The flexibility of the Pearson system makes it possible to model a wide range of source distributions including asymmetric distributions. The algorithm is designed especially for problems with asymmetric sources but it works for symmetric sources as well.
Package details 


Author  Juha Karvanen 
Date of publication  20090629 09:39:47 
Maintainer  Juha Karvanen <juha.karvanen@iki.fi> 
License  GPL2 
Version  1.24 
Package repository  View on CRAN 
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