The direct execution of the expectation-maximization algorithm using symbolic processing

This paper surveys a short study about using and applying symbolic processing to direct execution of the expectation-maximization algorithm. Formulas are derived in the manner defined by the expectation-maximization algorithm and how there are applied. Symbolic processing uses the set of equations on the same way that describe expectation maximization algorithm without any adaptation and loops of computation as usually done. The methodology of processing is described step-by-step for direct execution of expectation-maximization algorithm. Some of the advantages of symbolic processing are described in regard to numerical processing. Finally, numerical data are applied on the complete model and results are displayed.