资源大小： 166KB
发布时间： 2009-07-13
文件格式： pdf
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资源简介：

We describe the maximum-likelihood parameter estimation problem and how the Expectation-Maximization (EM) algorithm can be used for its solution. We first describe the abstractform of the EM algorithm as it is often given in the literature. We then develop the EM parameterestimation procedure for two applications: 1) finding the parameters of a mixture ofGaussian densities, and 2) finding the parameters of a hidden Markov model (HMM) (i.e.,the Baum-Welch algorithm) for both discrete and Gaussian


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