Computer Science ›› 2016, Vol. 43 ›› Issue (3): 72-74, 88.doi: 10.11896/j.issn.1002-137X.2016.03.014

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Subspace Clustering Based on Sequential Feature

CHEN Li-ping and GUO Gong-de   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Inspired by Tierney’s subspace clustering of the sequence data,a novel subspace clustering method based on sequential character was proposed.In the beginning,the lifting wavelet transform is applied to extract low-frequency information of the signal,and then a stronger special penalty term is applied to emphasize the similarity between adjacent samples,in which the penalty factor is automatically adjusted according to the noise.The proposed method performs better compared with the most characteristic sparse subspace clustering methods in experiment carried out on a synthetic data set and some data sets from real-world applications.

Key words: Sparse subspace clustering,Sequence feature,Penalty factor

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