SPARSE LOADING NOISY PCA USING AN l0 PENALTY

被引：0
|
作者：
Ulfarsson, M. O. [1 ]
Solo, V. [2 ]
机构：
[1] Univ Iceland, Dept Elect Eng, Reykjavik, Iceland
[2] Univ New South Wales, Sch Elect Engn, Sydney, NSW, Australia
来源：
2012 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2012年
关键词：
principal component analysis; sparsity; estimation; PRINCIPAL COMPONENT ANALYSIS;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
In this paper we present a novel model based sparse principal component analysis method based on the l(0) penalty. We develop an estimation method based on the generalized EM algorithm and iterative hard thresholding and an associated model selection method based on Bayesian information criterion (BIC). The method is compared to a previous sparse PCA method using both simulated data and DNA microarray data.
引用
收藏
页码：3597 / 3600
页数：4
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