Blind separation of fetal electrocardiograms by annealed expectation maximization

This work explores blind source separation of fetal electrocardiograms by annealed expectation maximization (AEM). The AEM method improves the traditional EM method by relaxation under an annealing process, which is recruited to avoid trappings of tremendous spurious local minima within an objective function that inversely measures quantitative performance of a demixing structure. The derived objective function depends on the demixing structure as well as a set of membership vectors that represent missing data toward encoding statistical dependency of retrieved independent sources. Under the annealing process, the derived E and M steps are iteratively performed to search for expectations of membership vectors and minimizers of the objective function. The state number of membership vectors is related to modulate discretization of observations. Its effects on extraction of fetal electrocardiograms and reliability of the AEM method for blind source separation are extensively explored by numerical simulations.