k-mean alignment for curve clustering
k-mean alignment for curve clustering
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DOI：
10.1016/j.csda.2009.12.008
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发表时间：
2010-05-01
影响因子：
1.8
通讯作者：
Vitelli, Valeria
中科院分区：
文献类型：
--
作者：
Sangalli, Laura M.;Secchi, Piercesare;Vitelli, Valeria
研究了曲线错位时的曲线聚类问题。提出了一种新的曲线聚类对齐算法。该方法有效地解耦了幅度和相位的变化，特别是能够检测出幅度簇，同时揭示了相位中的簇结构，指出了简单的曲线聚类或简单的曲线对齐无法捕捉到的特征。通过模拟研究和对实际数据的应用，说明了这一过程。(C)2010爱思唯尔B.V.保留所有权利。
The problem of curve clustering when curves are misaligned is considered. A novel algorithm is described, which jointly clusters and aligns curves. The proposed procedure efficiently decouples amplitude and phase variability; in particular, it is able to detect amplitude clusters while simultaneously disclosing clustering structures in the phase, pointing out features that can neither be captured by simple curve clustering nor by simple curve alignment. The procedure is illustrated via simulation studies and applications to real data. (C) 2010 Elsevier B.V. All rights reserved.