关键词: 贪心, 高斯混合模型, 隐含参量, 最大期望（EM）算法

Abstract: In order to solve the disadvantages of traditional EM algorithm which initial model component parameters need to preassign and the convergence speed follows the growth of sample numbers, an rapid greedy EM algorithm for Gaussian mixture model is proposed. This algorithm adopts greedy strategy and uses appropriate implicit parameters to accelerate the speed of convergence, which can precisely get the optimal solution of the model component?in a few iterations. In?experiments, compared with traditional EM algorithm, unsupervised EM algorithm and robust EM algorithm, the algorithm is robust, in addition, it can improve the efficiency of algorithm and the accuracy of the model component parameters.

Key words: greedy, Gaussian mixture model, implicit parameter, Expectation Maximization（EM） algorithm