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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Overdetermined Blind Source Separation by Gaussian Mixture Model
verfasst von : Yujia Wang, Yunfeng Xue
Erschienen in: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Verlag: Springer Berlin Heidelberg
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The blind separation of overdetermined mixtures, i.e., the case where more sensors than sources are available is considered in this paper. The contrast function for overdetermined blind source separation problem is presented, together with its gradient. An iterative method is proposed to solve the overdetermined blind source separation problem, where Gaussian mixture model is used to estimate the density of the unknown sources. The result of simulation demonstrates the efficiency of the proposed algorithm.