The modified MEXICO for ICA over finite fields
In 2007, a theory of ICA over finite fields emerged and an algorithm based on pairwise comparison of mixtures, called MEXICO, was developed to deal with this new problem. In this letter, we propose improvements in the method that, according to simulations in GF(2) and GF(3) scenarios, lead to a faster convergence and better separation results, increasing the application possibilities of the new theory in the context of large databases.
mexico ica finite fields information theory