Description: Expectation-Maximization
The EM (Expectation-Maximization) algorithm estimates the parameters of the multivariate probability density function in a form of the Gaussian mixture distribution with a specified number of mixtures.
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Author:luochentianshui@126.com |
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Description: This package contains Matlab m-files for learning finite Gaussian mixtures from sample data and performing data classification with Mahalanobis distance or Bayesian classifiers. Each class in training set is learned individually with one of the three variations of the Expectation Maximization algorithm: the basic EM algorithm with covariance fixing, the Figueiredo-Jain clustering algorithm and the greedy EM algorithm.
The basic EM and FJ algorithms can handle complex valued data directly, the greedy EM algorithm cannot.
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Author:李 |
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Search - Gaussian Mixtures EM