The EM algorithm in independent component analysis

We investigate two techniques for independent component analysis which use the expectation-maximization algorithm. Analysis and simulations show that convergence becomes extraordinarily slow for almost all cases, compared to other optimization techniques. The two alternatives considered are "adaptive overrelaxed EM" and Ucminf (a BFGS with soft line search), which both improves the convergence dramatically with little or no extra analytical work. We discuss the generality and perspectives of the findings.