计算机科学 ›› 2016, Vol. 43 ›› Issue (3): 72-74.doi: 10.11896/j.issn.1002-137X.2016.03.014
陈丽萍,郭躬德
CHEN Li-ping and GUO Gong-de
摘要: 受到Tierney的序列稀疏子空间聚类方法的启发,提出了一种新的基于顺序特性的子空间聚类方法。该方法先通过提升小波变换处理得到信号的低频信息;然后通过强调相邻样本之间的连续性来设置特殊的惩罚项,并根据噪声的大小自动调节惩罚因子;最后过滤系数矩阵中一些小的干扰系数。在人工合成和实际应用的数据集上的实验结果表明,与当前最具代表性的几种稀疏子空间聚类方法相比,所提方法具有较好的实验效果。
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