Robust on-line principal component analysis based on a fixed-point approach

被引：0
|
作者：
Rao, YN [1 ]
Principe, JC [1 ]
机构：
[1] Univ Florida, Computational Neuroengn Lab, Gainesville, FL 32611 USA
来源：
2002 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I-IV, PROCEEDINGS | 2002年
关键词：
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
Principal Component Analysis (PCA) is a widely used statistical tool in many signal-processing applications. In this paper we will present a new on-line algorithm for computing the principal components. The new algorithm belongs to a class of fixed-point methods. We mathematically investigate the convergence properties of the method and also verify the robustness of the algorithm with simulations.
引用
收藏
页码：981 / 984
页数：4
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