选择具有最大F -统计量的划分聚类方案。
The clustering scheme with the largest F-statistics is chosen.
基于这一问题本文通过构造统计量对所给的样本点进行选择,剔除对模型的构造有很大影响力的样本,从而获得一个相对合理的样本空间。
Based on this problem, this article selects the sample points by constructing statistics. First, it removes the outliers to have a relatively reasonable sample space.
在许多盲信号源分离算法中,大多需要选择合适的非线性函数或者需要计算信号的高阶统计量。
In many algorithms for blind source separation, most of them must select nonlinear function or compute high-order statistical values.
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