A modified PCA based on the minimum error entropy

Zhenhua Guo; Hong Yue; Hong Wang

doi:10.1109/ACC.2004.182879

A modified PCA based on the minimum error entropy

Zhenhua Guo, Hong Yue, Hong Wang

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Proceedings of the American Control Conference\|Proc Am Control Conf
Pages	3800-3801
Number of pages	1
Volume	4
DOIs	https://doi.org/10.1109/ACC.2004.182879
Publication status	Published - 2004
Event	Proceedings of the 2004 American Control Conference (AAC) - Boston, MA Duration: 1 Jul 2004 → …

Conference

Conference	Proceedings of the 2004 American Control Conference (AAC)
City	Boston, MA
Period	1/07/04 → …

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10.1109/ACC.2004.182879

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title = "A modified PCA based on the minimum error entropy",

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.",

author = "Zhenhua Guo and Hong Yue and Hong Wang",

year = "2004",

doi = "10.1109/ACC.2004.182879",

language = "English",

isbn = "0780383354",

volume = "4",

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booktitle = "Proceedings of the American Control Conference|Proc Am Control Conf",

note = "Proceedings of the 2004 American Control Conference (AAC) ; Conference date: 01-07-2004",

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AU - Yue, Hong

AU - Wang, Hong

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N2 - 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.

AB - 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.

U2 - 10.1109/ACC.2004.182879

DO - 10.1109/ACC.2004.182879

M3 - Conference contribution

SN - 0780383354

VL - 4

SP - 3800

EP - 3801

BT - Proceedings of the American Control Conference|Proc Am Control Conf

T2 - Proceedings of the 2004 American Control Conference (AAC)

Y2 - 1 July 2004

ER -

A modified PCA based on the minimum error entropy

Abstract

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