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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >EM algorithms for Gaussian mixtures with split-and-merge operation
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EM algorithms for Gaussian mixtures with split-and-merge operation

机译:具有拆分合并操作的高斯混合的EM算法

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摘要

In order to alleviate the problem of local convergence of the usual EM algorithm, a split-and-merge operation is introduced into the EM algorithm for Gaussian mixtures. The split-and-merge equations are first presented theoretically. These equations show that the merge operation is a well-posed problem, whereas the split operation is an ill-posed problem because it is the inverse procedure of the merge. Two methods for solving this ill-posed problem are developed through the singular value decomposition and the Cholesky decomposition. Accordingly, a new modified EM algorithm is constructed. Our experiments demonstrate that this algorithm is efficient for unsupervised color image segmentation. (C) 2003 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved. [References: 27]
机译:为了缓解常规EM算法的局部收敛性问题,针对高斯混合的EM算法引入了拆分合并操作。首先从理论上介绍了拆分合并方程。这些方程式表明合并操作是一个适切的问题,而拆分操作则是一个不适定的问题,因为它是合并的逆过程。通过奇异值分解和Cholesky分解,开发了两种解决该不适定问题的方法。因此,构造了新的改进的EM算法。我们的实验表明,该算法对于无监督的彩色图像分割是有效的。 (C)2003模式识别学会。由Elsevier Science Ltd.出版。保留所有权利。 [参考:27]

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