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电子学报  2014 

多线性鲁棒主成分分析

DOI: 10.3969/j.issn.0372-2112.2014.08.004, PP. 1480-1486

Keywords: 多线性鲁棒主成分分析,鲁棒主成分分析,低秩,核范数最小化,增广拉格朗日乘子法

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Abstract:

鲁棒主成分分析(RPCA)是恢复低秩与稀疏成分的一种非常有效的方法.本文将RPCA推广到张量情形,提出了多线性鲁棒主成分分析(MRPCA)框架.首先建立了MRPCA模型,即最小化张量核范数与l1范数的加权组合.然后使用增广拉格朗日乘子法求解上述张量核范数优化问题.实验结果证实:对于具有多线性结构的数据,MRPCA比RPCA更加鲁棒.

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