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Covariance Based Learning Algorithm for Gaussian Mixture Model
Authors
姜青山
廖晓锋
范修斌
Publication date
1 January 2013
Publisher
Abstract
对混合高斯模型参数估计问题的算法通常是基于期望最大(Expectation Maximization)给出的.在混合高斯模型的因素协方差矩阵已知、因素各分量独立的前提下,给出了基于协方差矩阵的机器学习算法,简称CVB(Covari-ance Based)算法,并进行了一定的数学分析.最后给出了与期望最大算法的实验结果比较.实验结果表明,在该条件下,基于协方差的算法优于期望最大算法
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Institute Of Software, Chinese Academy Of Sciences
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Last time updated on 30/12/2017