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Blind Separation Using Characteristic Function Based Criterion

机译:使用基于特征函数的准则进行盲分离

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摘要

We propose a novel method for blind separation of statistically independent sources. The objective function used in the separation is based on the fact that the joint characteristic function factors to a product of the characteristic functions of the independent marginals. New algorithm for minimizing the above criterion is derived as well. It estimates the separating matrix by ensuring that the sources are pairwise independent. The theoretical characteristic functions in the objective function are replaced by their empirical counterparts. Simulation studies demonstrating the reliable performance of the proposed method in separating many different types of sources are presented. In particular, distributions often encountered in wireless communication applications are employed in the examples.
机译:我们提出了一种用于统计独立来源盲分离的新方法。分离中使用的目标函数基于以下事实:联合特征函数是独立边际特征函数的乘积。还导出了用于最小化上述标准的新算法。它通过确保源成对独立来估计分离矩阵。目标函数中的理论特征函数被其经验对应物替代。仿真研究表明了所提方法在分离许多不同类型的源中的可靠性能。特别地,在示例中采用在无线通信应用中经常遇到的分布。

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