DocumentCode
425170
Title
A modified PCA based on the minimum error entropy
Author
Guo, Zhenhua ; Yue, Hong ; Wang, Hong
Author_Institution
Sch. of Mech. Sci. & Eng., Huazhong Univ. of Sci. & Technol., Hubei, China
Volume
4
fYear
2004
fDate
June 30 2004-July 2 2004
Firstpage
3800
Abstract
Conventional principal component analysis (PCA) minimizes the total error variance, which may be inappropriate for the non-Gaussian distribution systems. In this paper the entropy is proposed as a more general index for PCA model, and then a modified PCA with the optimization for the minimum error entropy via a genetic algorithm (GA) is addressed.
Keywords
genetic algorithms; least mean squares methods; minimum entropy methods; principal component analysis; GA optimization; genetic algorithm; minimum error entropy; modified PCA; nonGaussian distribution systems; principal component analysis; total error variance;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2004. Proceedings of the 2004
Conference_Location
Boston, MA, USA
ISSN
0743-1619
Print_ISBN
0-7803-8335-4
Type
conf
Filename
1384504
Link To Document