Some Applications of Expectation Maximization Algorithm

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Expectation maximization (EM) algorithm is a popular and powerful mathematical method for statistical parameter estimation in case that there exist both observed data and hidden data. This book focuses on applications of EM in which the implicit relationship is essential to connect observed data and hidden data. In other words, such applications reinforce EM which in turn extends estimation methods like maximum likelihood estimation (MLE) or moment method.