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IEEE Trans Pattern Anal Mach Intell. 2008 Sep;30(9):1672-80. doi: 10.1109/TPAMI.2008.114.

Principal component analysis based on l1-norm maximization.

Author information

1
Division of Electrical and Computer Engineering, Ajou University, Suwon, Korea. nojunk@ieee.org

Abstract

A method of principal component analysis (PCA) based on a new L1-norm optimization technique is proposed. Unlike conventional PCA which is based on L2-norm, the proposed method is robust to outliers because it utilizes L1-norm which is less sensitive to outliers. It is invariant to rotations as well. The proposed L1-norm optimization technique is intuitive, simple, and easy to implement. It is also proven to find a locally maximal solution. The proposed method is applied to several datasets and the performances are compared with those of other conventional methods.

PMID:
18617723
DOI:
10.1109/TPAMI.2008.114
[Indexed for MEDLINE]

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