论文标题
$ k $ - 表示为正定矩阵的$ k $ - 并应用于雷达图像序列的聚类
$k$-means on Positive Definite Matrices, and an Application to Clustering in Radar Image Sequences
论文作者
论文摘要
我们陈述了$ k $的理论属性 - 在非欧几里得空间中的对称正定矩阵（SPD）矩阵的聚类，可提供这些数据的自然和有利表示。然后，我们通过其有限的落叶自动助力矩阵为这种方法提供了这种方法的新应用，以一系列合成孔径雷达图像的时间序列聚类。
We state theoretical properties for $k$-means clustering of Symmetric Positive Definite (SPD) matrices, in a non-Euclidean space, that provides a natural and favourable representation of these data. We then provide a novel application for this method, to time-series clustering of pixels in a sequence of Synthetic Aperture Radar images, via their finite-lag autocovariance matrices.
